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X5;ND|Sei?^d;տfPG%u&!O߿-pRe5|?{K"^/ܿBðI p?V="n:,7SFI?؏l{ z.ؿWAr+}W?Zptg+N}T?3uobe|yDq?-?O?|ٵ):*=5>r'R鿔}Uﱄ"?"Fs?bC.!\?{|u{9S~?\v$j &#ۿq˿.>_-li'$l[?}h0m2iSH ?PP?U"Ֆf?17uIS  eT?VjɔIW`пCTe}i3Ք=-ۿ)߆f|z}X?(7q2d2ؿ#f7DT?>@FInj?ƿ/_sĝ6ؤӿhڗ¢up?C;dC?V 0{Lhr_x5?,Rn?&yYi ?m }'Sޱ@p0O=?E;r),-bRk[QJ&?&hcXp?d>$qQ,RTZIk=]2?1w@K޿›YF:47LLj6%^E ?b#WO`w %]걋cOwb ?/_b_4 gV?s1Ԏ 7awܿyfu%B]?kןaq h,Ͽa`)e3׿~$Cg4ku?d{x+ӿ0o4븘B;]?-nnTx+7/??&gGĝV Ͽu/|?s:WsqqqqVZkVZ?hB2r* ySD?* ySDoa,c剮/"/}ykʩ?|_)'*4W #Y??1 r?,(? kD:殨#ގ¼ ?LI8tw4ۿQvsdȌ4<4?'AVoxݿN=WmF:>?XaWf@U? !)mF/Ϝؿkh9# Q?qܥʿ:ٝ^EHhҿ GEmm?s7|I&"*ۃ7)Ͽ%AlJ&?$:zX&?ON i0t?ʿ];Rid?UUUUUUUUUUUUUUUUUUUUUUUUUUUU?s:WsKh/Kh/?8slU:q?(M{YsrovM@R2|/H?\h/:*epS%n}*!OkLY/K!m?jeOe-_{运}2tzE?Y7\՗`?1eǗ!-*ac$m?)e=޽ۿ4"PyB@spݿ)؛tecu?qD66TpaٿXr; ^?uIފiu{?&:C$);9ԿQ!®iC?h ?(̿o}j'ο4SOH?<ٽ=|ʿJee!A6qu?Zw2g,?"?^O s_ſ}9I 0ED?a`Z/X\Fֽ>(/tB.NϘ"A#wA '/AJdAPBkAg8JA`u;^"AJ@P+@wݳ|@c3@KwP?E!jMx?gId`cF0vWtHo]vH?4-XVa(`?Cuo ?ps ( ?n+Css֥?$(䈷Xȥb2-Ѫ&idG%sD:{T# Y&Z?g2ZA?AYobOtT?PqW? 4#q",(5Nd.љ?YEy]!&XÿB) ~i !LGQm5Qjm(1oX7eםVT?7egQPQ*Xl?3LTG?I Ŏ4H1^? fleԽ=?0lnoѿ{|WW?Wb|pIy'_#kFP 0?Mv .zB|G7?1;hGs?&({5XeJ?VT4% 5?Ibv[޿d8X 4Xv??#>UX6@p̱ bsmX@,a7<b1@RSdtQ(ѽ K@O`,}T@pX ?=j"]7?Dcj?!:Ӟr} vXFYX@sO&OD˴x'b[?YMX!0'pS^?LR XGvsY?|ֺiOȘ$? qkrZ e? U;Bu.z] :?c}d l ‡e.rm?qa[0Uwv?Q{~ip(o@PʻaUT@1:MgTe6䒖ʭ_JBm.޽O|@9(W@j:uZ@, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >; SrcXprType = Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >; Functor = Eigen::internal::sub_assign_op]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >; SrcXprType = Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >; Functor = Eigen::internal::add_assign_op]Eigen::CwiseNullaryOp::CwiseNullaryOp(Eigen::Index, Eigen::Index, const NullaryOp&) [with NullaryOp = Eigen::internal::scalar_constant_op; PlainObjectType = Eigen::Matrix; Eigen::Index = long int]Eigen::CwiseBinaryOp::CwiseBinaryOp(const Lhs&, const Rhs&, const BinaryOp&) [with BinaryOp = Eigen::internal::scalar_product_op; LhsType = const Eigen::CwiseUnaryOp::type>::value, void>::type>::apply(const T&) [with F = stan::math::sign_fun; T = Eigen::Array]::, const Eigen::Array >; RhsType = const Eigen::CwiseNullaryOp, const Eigen::Array >; Eigen::CwiseBinaryOp::Lhs = Eigen::CwiseUnaryOp::type>::value, void>::type>::apply(const T&) [with F = stan::math::sign_fun; T = Eigen::Array]::, const Eigen::Array >; Eigen::CwiseBinaryOp::Rhs = Eigen::CwiseNullaryOp, const Eigen::Array >]Eigen::CwiseBinaryOp::CwiseBinaryOp(const Lhs&, const Rhs&, const BinaryOp&) [with BinaryOp = Eigen::internal::scalar_difference_op; LhsType = const Eigen::ArrayWrapper >; RhsType = const Eigen::CwiseNullaryOp, const Eigen::Array >; Eigen::CwiseBinaryOp::Lhs = Eigen::ArrayWrapper >; Eigen::CwiseBinaryOp::Rhs = Eigen::CwiseNullaryOp, const Eigen::Array >]Eigen::CwiseBinaryOp::CwiseBinaryOp(const Lhs&, const Rhs&, const BinaryOp&) [with BinaryOp = Eigen::internal::scalar_product_op; LhsType = const Eigen::CwiseNullaryOp, const Eigen::Array >; RhsType = const Eigen::Array; Eigen::CwiseBinaryOp::Lhs = Eigen::CwiseNullaryOp, const Eigen::Array >; Eigen::CwiseBinaryOp::Rhs = Eigen::Array]Eigen::CwiseBinaryOp::CwiseBinaryOp(const Lhs&, const Rhs&, const BinaryOp&) [with BinaryOp = Eigen::internal::scalar_difference_op; LhsType = const Eigen::Array; RhsType = const Eigen::CwiseNullaryOp, const Eigen::Array >; Eigen::CwiseBinaryOp::Lhs = Eigen::Array; Eigen::CwiseBinaryOp::Rhs = Eigen::CwiseNullaryOp, const Eigen::Array >]Eigen::CwiseBinaryOp::CwiseBinaryOp(const Lhs&, const Rhs&, const BinaryOp&) [with BinaryOp = Eigen::internal::scalar_product_op; LhsType = const Eigen::CwiseUnaryOp, const Eigen::Array >; RhsType = const Eigen::CwiseNullaryOp, const Eigen::Array >; Eigen::CwiseBinaryOp::Lhs = Eigen::CwiseUnaryOp, const Eigen::Array >; Eigen::CwiseBinaryOp::Rhs = Eigen::CwiseNullaryOp, const Eigen::Array >]Eigen::CwiseNullaryOp::CwiseNullaryOp(Eigen::Index, Eigen::Index, const NullaryOp&) [with NullaryOp = Eigen::internal::scalar_constant_op >; PlainObjectType = Eigen::Matrix, -1, 1>; Eigen::Index = long int]Eigen::CwiseNullaryOp::CwiseNullaryOp(Eigen::Index, Eigen::Index, const NullaryOp&) [with NullaryOp = Eigen::internal::scalar_constant_op; PlainObjectType = Eigen::Array; Eigen::Index = long int]Eigen::MapBase::MapBase(Eigen::MapBase::PointerType, Eigen::Index, Eigen::Index) [with Derived = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; Eigen::MapBase::PointerType = stan::math::var_value*; Eigen::Index = long int]Eigen::CwiseNullaryOp::CwiseNullaryOp(Eigen::Index, Eigen::Index, const NullaryOp&) [with NullaryOp = Eigen::internal::scalar_constant_op; PlainObjectType = Eigen::Matrix; Eigen::Index = long int]void Eigen::PlainObjectBase::resize(Eigen::Index, Eigen::Index) [with Derived = Eigen::Array; Eigen::Index = long int]void* Eigen::internal::aligned_malloc(std::size_t)void Eigen::PlainObjectBase::resize(Eigen::Index, Eigen::Index) [with Derived = Eigen::Matrix; Eigen::Index = long int]void Eigen::PlainObjectBase::resize(Eigen::Index, Eigen::Index) [with Derived = Eigen::Matrix, -1, 1>; Eigen::Index = long int]??@@8@^@@@@&AKAAA2A(;L4BuwsBuwB7Bs6Ch0{CZAC Ƶ;(DlYaRwNDΤ5D{zhRlD!a?@)E~tE凗Egi=-FQ[F -n'F3 VF3 VIGAsb!G3xG]>H޲HH_Tt7IdaIp]IDh,6JHH Jh9/JLp8;K3KKA K$sPDL,xL;DL%{RMG#uMc:M)NZ3cN;N(I_O@5&yOaO#L4Pl]öP 'WP~ϸPQ2C3QJ4xRJ4xoR.h2R`>0S M1|SaS91KTTmTi3ZMUfyW{Uy>B/ULRBV3q VlF WĺL/nW С\dW̼Ws6X픐aXf>~YgY"𤽳Y=t3ZaZyy[r>g[>t0K U[aE6\R*Q\=ٴ]syQp]1"]đ}jA^_tک^Gc׍c_x b}_4(ȵ_;ϘfQ`ܕN0`@T&Vt%a#aGPÃap v[fbԒ Vb0{_>c,$ccCKld ؛8>d/GKZd?0[eϗe-5fH㴢f/-gq1Ov~g 2c$g!rAYh6h٩c_6i7,&ia(j+*^jzj?@Sbk k@Al@lcÀ "m8q.QmnUsnD}Rn#F)Uo.oU;A7p.џ9pMC2q&0}qUjk&r!S͟qr9D}Hɼr8 Vs~pso,MxxV&,)5y'wyU zKrJzގ=_] {Wrq{[v0{h~Gi|hx|;7;U})lgˈ}w,#]A/:Y0Y$u dA}1G RjA8,HxhfkpAWr4նOKvAUi%M&}AC<{:GkAo N ƉA]K`5rm[A0cd:<-pAL]1SO;{ݜAeaCGX9AÛ$]*AԔSJ'=AQ& !c|AWz+6CPAfv`0eQdkAtҦ7KA_CMkA;ǘA~Ӧ .r{AQ3Z@Y٧A]DEO'A1XFks4{86A2E/.Ap=@\gAmsZ bilBڻTRi@]9d B:܄#FCeiEWB~M9p<,h-PBSD1~ 5<B]ZX`e&B Z6.H- k%-B\gn3B:%a[ṢJ>:BiS%L1VABk[n#HBUxm%rĽNBZ]eP[ UBϏؖ0P||\B`%M+ʂXPcBZJJ{|Nj0N+jB҂? qBs7e DdwBT 3F~BQ zhY"B7CW!An}BZoNMb _ 8eB$kbRB63gPBB6kb5B[W{=,BCKFl 4%B&2._ : Ba4h8 S]Ba4h8 S]BnyxP:6 B,Zyg"%B?y T}+B ^W&C K[5B @.EqABx]3 mPBXmr}bB޵AJTyCaj6 C7nNi:$CBr\-,[WCg(Ik Cz@&\2e'Co&,~zCԇ;.CRx#`5CN_&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseNullaryOp, Eigen::Matrix >; T1 = double; T2 = double]Eigen::MapBase::MapBase(Eigen::MapBase::PointerType, Eigen::Index) [with Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >; Eigen::MapBase::PointerType = double*; Eigen::Index = long int]Eigen::MapBase::MapBase(Eigen::MapBase::PointerType, Eigen::Index) [with Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >; Eigen::MapBase::PointerType = int*; Eigen::Index = long int]Eigen::MapBase::MapBase(Eigen::MapBase::PointerType, Eigen::Index, Eigen::Index) [with Derived = Eigen::Map >; Eigen::MapBase::PointerType = double*; Eigen::Index = long int]void Eigen::PlainObjectBase::resize(Eigen::Index, Eigen::Index) [with Derived = Eigen::Matrix; Eigen::Index = long int]void Eigen::DenseBase::resize(Eigen::Index, Eigen::Index) [with Derived = Eigen::Map >; Eigen::Index = long int]void Eigen::DenseBase::resize(Eigen::Index, Eigen::Index) [with Derived = Eigen::Block, 1, -1, false>; Eigen::Index = long int]Eigen::internal::variable_if_dynamic::variable_if_dynamic(T) [with T = long int; int Value = 1]void Eigen::PlainObjectBase::resize(Eigen::Index, Eigen::Index) [with Derived = Eigen::Matrix; Eigen::Index = long int]Eigen::CwiseNullaryOp::CwiseNullaryOp(Eigen::Index, Eigen::Index, const NullaryOp&) [with NullaryOp = Eigen::internal::scalar_constant_op; PlainObjectType = Eigen::Matrix; Eigen::Index = long int]Eigen::MapBase::MapBase(Eigen::MapBase::PointerType, Eigen::Index, Eigen::Index) [with Derived = Eigen::Block, 1, -1, false>; Eigen::MapBase::PointerType = double*; Eigen::Index = long int]Eigen::Block::Block(XprType&, Eigen::Index) [with XprType = Eigen::Matrix; int BlockRows = 1; int BlockCols = -1; bool InnerPanel = false; Eigen::Index = long int]`MMM@MxMMMxMMXM@MMMMMXMMM`M(MMMM@MxMxM MMXMM(MM`M8MpMMMMMMMMMPMMMM0MhMMMMMHMMMMMM@MxMMM MXMMMM@MMMM8MpM0MMMM MMXMMMMMHMMPMMMMMM8MMxMvoid Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; T1 = double; T2 = double]Eigen::Product::Product(const Lhs&, const Rhs&) [with _Lhs = Eigen::Map >; _Rhs = Eigen::Matrix; int Option = 0; Eigen::Product::Lhs = Eigen::Map >; Eigen::Product::Rhs = Eigen::Matrix]Eigen::CwiseNullaryOp::CwiseNullaryOp(Eigen::Index, Eigen::Index, const NullaryOp&) [with NullaryOp = Eigen::internal::scalar_constant_op; PlainObjectType = const Eigen::Array; Eigen::Index = long int]Eigen::CwiseBinaryOp::CwiseBinaryOp(const Lhs&, const Rhs&, const BinaryOp&) [with BinaryOp = Eigen::internal::scalar_product_op; LhsType = const Eigen::Matrix; RhsType = const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper >, Eigen::Matrix, 0> > > >; Eigen::CwiseBinaryOp::Lhs = Eigen::Matrix; Eigen::CwiseBinaryOp::Rhs = Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper >, Eigen::Matrix, 0> > > >]Eigen::MapBase::MapBase(Eigen::MapBase::PointerType, Eigen::Index) [with Derived = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; Eigen::MapBase::PointerType = stan::math::var_value*; Eigen::Index = long int]M PMMMEigen::CwiseBinaryOp::CwiseBinaryOp(const Lhs&, const Rhs&, const BinaryOp&) [with BinaryOp = Eigen::internal::scalar_product_op; LhsType = const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >; RhsType = const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >; Eigen::CwiseBinaryOp::Lhs = Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >; Eigen::CwiseBinaryOp::Rhs = Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >; Functor = Eigen::internal::add_assign_op]void Eigen::DenseBase::resize(Eigen::Index, Eigen::Index) [with Derived = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; Eigen::Index = long int]Eigen::CwiseNullaryOp::CwiseNullaryOp(Eigen::Index, Eigen::Index, const NullaryOp&) [with NullaryOp = Eigen::internal::scalar_constant_op; PlainObjectType = const Eigen::Array; Eigen::Index = long int]Eigen::CwiseBinaryOp::CwiseBinaryOp(const Lhs&, const Rhs&, const BinaryOp&) [with BinaryOp = Eigen::internal::scalar_product_op; LhsType = const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >; RhsType = const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >; Eigen::CwiseBinaryOp::Lhs = Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >; Eigen::CwiseBinaryOp::Rhs = Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >]Eigen::CwiseBinaryOp::CwiseBinaryOp(const Lhs&, const Rhs&, const BinaryOp&) [with BinaryOp = Eigen::internal::scalar_product_op; LhsType = const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >; RhsType = const Eigen::Map, 0, Eigen::Stride<0, 0> >; Eigen::CwiseBinaryOp::Lhs = Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >; Eigen::CwiseBinaryOp::Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >]Eigen::MapBase::MapBase(Eigen::MapBase::PointerType, Eigen::Index, Eigen::Index) [with Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >; Eigen::MapBase::PointerType = double*; Eigen::Index = long int]Eigen::CwiseBinaryOp::CwiseBinaryOp(const Lhs&, const Rhs&, const BinaryOp&) [with BinaryOp = Eigen::internal::scalar_product_op; LhsType = const Eigen::Map, 0, Eigen::Stride<0, 0> >; RhsType = const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >; Eigen::CwiseBinaryOp::Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Eigen::CwiseBinaryOp::Rhs = Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >]XprType& Eigen::CommaInitializer::finished() [with XprType = Eigen::Matrix]void Eigen::PlainObjectBase::resize(Eigen::Index) [with Derived = Eigen::Matrix, -1, 1>; Eigen::Index = long int]Eigen::MapBase::MapBase(Eigen::MapBase::PointerType, Eigen::Index, Eigen::Index) [with Derived = Eigen::Block, -1, 1>, -1, 1, false>; Eigen::MapBase::PointerType = stan::math::var_value*; Eigen::Index = long int]Eigen::Block::Block(XprType&, Eigen::Index, Eigen::Index, Eigen::Index, Eigen::Index) [with XprType = Eigen::Matrix, -1, 1>; int BlockRows = -1; int BlockCols = 1; bool InnerPanel = false; Eigen::Index = long int]Eigen::MapBase::MapBase(Eigen::MapBase::PointerType, Eigen::Index) [with Derived = Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> >; Eigen::MapBase::PointerType = const stan::math::var_value*; Eigen::Index = long int]void Eigen::DenseBase::resize(Eigen::Index, Eigen::Index) [with Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >; Eigen::Index = long int]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Array; SrcXprType = Eigen::CwiseUnaryOp [with auto:13 = Eigen::ArrayWrapper, -1, 1> >; EigMat = Eigen::ArrayWrapper, -1, 1> >; stan::require_eigen_t* = 0u; stan::require_not_st_arithmetic* = 0u]::, const Eigen::ArrayWrapper, -1, 1> > >; T1 = double; T2 = double]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Array; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >; T1 = double; T2 = double]typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]Eigen::CwiseBinaryOp::CwiseBinaryOp(const Lhs&, const Rhs&, const BinaryOp&) [with BinaryOp = Eigen::internal::scalar_product_op; LhsType = const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >; RhsType = const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >; Eigen::CwiseBinaryOp::Lhs = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >; Eigen::CwiseBinaryOp::Rhs = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Array; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >; T1 = double; T2 = double]typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >; typename Eigen::internal::traits::Scalar = double]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Array; SrcXprType = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >; T1 = double; T2 = double]Eigen::CwiseBinaryOp::CwiseBinaryOp(const Lhs&, const Rhs&, const BinaryOp&) [with BinaryOp = Eigen::internal::scalar_product_op; LhsType = const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >; RhsType = const Eigen::Array; Eigen::CwiseBinaryOp::Lhs = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >; Eigen::CwiseBinaryOp::Rhs = Eigen::Array]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Array; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; T1 = double; T2 = double]Eigen::CwiseBinaryOp::CwiseBinaryOp(const Lhs&, const Rhs&, const BinaryOp&) [with BinaryOp = Eigen::internal::scalar_product_op; LhsType = const Eigen::Array; RhsType = const Eigen::Array; Eigen::CwiseBinaryOp::Lhs = Eigen::Array; Eigen::CwiseBinaryOp::Rhs = Eigen::Array]Eigen::Product::Product(const Lhs&, const Rhs&) [with _Lhs = Eigen::Map >; _Rhs = Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >; int Option = 0; Eigen::Product::Lhs = Eigen::Map >; Eigen::Product::Rhs = Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >; T1 = double; T2 = double]Eigen::CwiseBinaryOp::CwiseBinaryOp(const Lhs&, const Rhs&, const BinaryOp&) [with BinaryOp = Eigen::internal::scalar_sum_op; LhsType = const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >; RhsType = const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >; Eigen::CwiseBinaryOp::Lhs = Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >; Eigen::CwiseBinaryOp::Rhs = Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >]Eigen::CwiseBinaryOp::CwiseBinaryOp(const Lhs&, const Rhs&, const BinaryOp&) [with BinaryOp = Eigen::internal::scalar_difference_op; LhsType = const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >; RhsType = const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >; Eigen::CwiseBinaryOp::Lhs = Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >; Eigen::CwiseBinaryOp::Rhs = Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >]void Eigen::PlainObjectBase::resize(Eigen::Index) [with Derived = Eigen::Array; Eigen::Index = long int]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Array; SrcXprType = Eigen::Matrix; T1 = double; T2 = double]Eigen::CwiseBinaryOp::CwiseBinaryOp(const Lhs&, const Rhs&, const BinaryOp&) [with BinaryOp = Eigen::internal::scalar_difference_op; LhsType = const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >; RhsType = const Eigen::Array; Eigen::CwiseBinaryOp::Lhs = Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >; Eigen::CwiseBinaryOp::Rhs = Eigen::Array]Eigen::CwiseBinaryOp::CwiseBinaryOp(const Lhs&, const Rhs&, const BinaryOp&) [with BinaryOp = Eigen::internal::scalar_difference_op; LhsType = const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >; RhsType = const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper >, Eigen::Matrix, 0> > > > > >; Eigen::CwiseBinaryOp::Lhs = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >; Eigen::CwiseBinaryOp::Rhs = Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper >, Eigen::Matrix, 0> > > > > >]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Array; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper >, Eigen::Matrix, 0> > > > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >; T1 = double; T2 = double]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseUnaryOp::type>::value, void>::type>::apply(const T&) [with F = stan::math::inv_logit_fun; T = Eigen::CwiseBinaryOp, const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper >, Eigen::Matrix, 0> > > >, const Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper >, Eigen::Matrix, 0> > > > > >]::, const Eigen::CwiseBinaryOp, const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper >, Eigen::Matrix, 0> > > >, const Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper >, Eigen::Matrix, 0> > > > > > > >; T1 = double; T2 = double]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::Matrix >; T1 = double; T2 = double]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper >, Eigen::Matrix, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper >, Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::Matrix >, 0> > > > >; T1 = double; T2 = double]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >; T1 = double; T2 = double]Eigen::MapBase::MapBase(Eigen::MapBase::PointerType, Eigen::Index, Eigen::Index) [with Derived = Eigen::Block, -1, 1, true>; Eigen::MapBase::PointerType = double*; Eigen::Index = long int]Eigen::Product::Product(const Lhs&, const Rhs&) [with _Lhs = Eigen::Transpose > >; _Rhs = Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >; int Option = 0; Eigen::Product::Lhs = Eigen::Transpose > >; Eigen::Product::Rhs = Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >; SrcXprType = Eigen::Matrix; Functor = Eigen::internal::add_assign_op]Eigen::MapBase::MapBase(Eigen::MapBase::PointerType, Eigen::Index, Eigen::Index) [with Derived = Eigen::Block >, -1, 1, true>; Eigen::MapBase::PointerType = double*; Eigen::Index = long int]static void Eigen::internal::checkTransposeAliasing_impl::run(const Derived&, const OtherDerived&) [with Derived = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; OtherDerived = Eigen::Matrix; bool MightHaveTransposeAliasing = true]Eigen::Product::Product(const Lhs&, const Rhs&) [with _Lhs = Eigen::Map >; _Rhs = Eigen::CwiseUnaryOp [with auto:33 = const Eigen::Matrix, -1, 1>; T = const Eigen::Matrix, -1, 1>&; = void; = void]::, const Eigen::Matrix, -1, 1> >; int Option = 0; Eigen::Product::Lhs = Eigen::Map >; Eigen::Product::Rhs = Eigen::CwiseUnaryOp [with auto:33 = const Eigen::Matrix, -1, 1>; T = const Eigen::Matrix, -1, 1>&; = void; = void]::, const Eigen::Matrix, -1, 1> >]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseUnaryOp [with auto:33 = const Eigen::Matrix, -1, 1>; T = const Eigen::Matrix, -1, 1>&; = void; = void]::, const Eigen::Matrix, -1, 1> >; T1 = double; T2 = double]Eigen::CwiseBinaryOp::CwiseBinaryOp(const Lhs&, const Rhs&, const BinaryOp&) [with BinaryOp = Eigen::internal::scalar_difference_op; LhsType = const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >; RhsType = const Eigen::ArrayWrapper [with auto:33 = const Eigen::Matrix, -1, 1>; T = const Eigen::Matrix, -1, 1>&; = void; = void]::, const Eigen::Matrix, -1, 1> > >; Eigen::CwiseBinaryOp::Lhs = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >; Eigen::CwiseBinaryOp::Rhs = Eigen::ArrayWrapper [with auto:33 = const Eigen::Matrix, -1, 1>; T = const Eigen::Matrix, -1, 1>&; = void; = void]::, const Eigen::Matrix, -1, 1> > >]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >; T1 = double; T2 = double]Eigen::Product::Product(const Lhs&, const Rhs&) [with _Lhs = Eigen::Transpose >; _Rhs = Eigen::Map >; int Option = 0; Eigen::Product::Lhs = Eigen::Transpose >; Eigen::Product::Rhs = Eigen::Map >]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >; Functor = Eigen::internal::add_assign_op]stan/lib/stan_math/lib/eigen_3.3.9/Eigen/src/Core/AssignEvaluator.hdst.rows() == src.rows() && dst.cols() == src.cols()stan/lib/stan_math/lib/eigen_3.3.9/Eigen/src/Core/CwiseNullaryOp.hrows >= 0 && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == rows) && cols >= 0 && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == cols)stan/lib/stan_math/lib/eigen_3.3.9/Eigen/src/Core/CwiseBinaryOp.haLhs.rows() == aRhs.rows() && aLhs.cols() == aRhs.cols()basic_string::_M_construct null not validstan/lib/stan_math/lib/eigen_3.3.9/Eigen/src/Core/MapBase.h(dataPtr == 0) || ( rows >= 0 && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == rows) && cols >= 0 && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == cols))prophet_modelstanc_version = stanc3 v2.30.0stancflags = kdeltasigma_obsbetatrendstan/lib/stan_math/lib/eigen_3.3.9/Eigen/src/Core/PlainObjectBase.h(!(RowsAtCompileTime!=Dynamic) || (rows==RowsAtCompileTime)) && (!(ColsAtCompileTime!=Dynamic) || (cols==ColsAtCompileTime)) && (!(RowsAtCompileTime==Dynamic && MaxRowsAtCompileTime!=Dynamic) || (rows<=MaxRowsAtCompileTime)) && (!(ColsAtCompileTime==Dynamic && MaxColsAtCompileTime!=Dynamic) || (cols<=MaxColsAtCompileTime)) && rows>=0 && cols>=0 && "Invalid sizes when resizing a matrix or array."stan/lib/stan_math/lib/eigen_3.3.9/Eigen/src/Core/util/Memory.h(size<16 || (std::size_t(result)%16)==0) && "System's malloc returned an unaligned pointer. Compile with EIGEN_MALLOC_ALREADY_ALIGNED=0 to fallback to handmade alignd memory allocator.": accessing element out of range. index out of range; container is empty and cannot be indexedexpecting index to be between and Found negative dimension size in variable declaration; variable=; dimension size expression=; expression value=basic_string::replace%s: __pos (which is %zu) > this->size() (which is %zu)basic_string::append [origin: ]Exception: bad_allocbad_castbad_exceptionbad_typeidunknown original type%f, but must be greater than or equal to is dst.rows() == dstRows && dst.cols() == dstColsint variable contained non-int valuesvariable does not existint; processing stage=; variable name=; base type=mismatch in number dimensions declared and found in context; dims declared=; dims found=mismatch in dimension declared and found in context; position=) must match in size%dvecSize >= 0, but must be is nonnegativeIn serializer: Storage capacity [%lu] exceeded while writing value of size [] from position []. This is an internal error, if you see it please report it as an issue on the Stan github repository.) and ( assign columnsright hand side columns assign rowsmatrixright hand side rowsstan/lib/stan_math/lib/eigen_3.3.9/Eigen/src/Core/DenseBase.hrows == this->rows() && cols == this->cols() && "DenseBase::resize() does not actually allow to resize."stan/lib/stan_math/lib/eigen_3.3.9/Eigen/src/Core/util/XprHelper.hv == T(Value)Unknown function operating on type %1%Cause unknownError in function long double%1%numeric overflowboost::math::erfc<%1%>(%1%, %1%)Result of incomplete gamma function is too large to represent.boost::math::detail::full_igamma_prefix<%1%>(%1%, %1%)Overflow Errorboost::math::expm1<%1%>(%1%)Cause unknown: error caused by bad argument with value %1%ATSa_rowrep_matrixcolsassigning variable Arep_vectorassigning variable a_rowvector[uni] indexingmatrix[uni] assign columnsright hand side sizestan/lib/stan_math/lib/eigen_3.3.9/Eigen/src/Core/Block.h(i>=0) && ( ((BlockRows==1) && (BlockCols==XprType::ColsAtCompileTime) && i(%1%)For non-integral exponent, expected base > 0 but got %1%Evaluation of tgamma at a negative integer %1%.Result of tgamma is too large to represent.boost::math::itrunc<%1%>(%1%)boost::math::tgamma<%1%>(%1%)Series evaluation exceeded %1% iterations, giving up now.boost::math::detail::lower_gamma_series<%1%>(%1%)log1pmx(x) requires x > -1, but got x = %1%.Got x == %1%, but x must be > 0, complex result not supported.boost::math::bessel_y1<%1%>(%1%,%1%)Evaluation of lgamma at a negative integer %1%.Evaluation of lgamma at %1%.boost::math::lgamma<%1%>(%1%)boost::math::erf<%1%>(%1%, %1%)Argument a to the incomplete gamma function must be greater than zero (got a=%1%).Argument x to the incomplete gamma function must be >= 0 (got x=%1%).log1p(x) requires x > -1, but got x = %1%.log1p<%1%>(%1%)boost::math::tgamma1pm1<%!%>(%1%)boost::math::tgamma<%1%>(%1%,%1%)Argument a must be finite, but got %1%Argument b must be finite, but got %1%Range arguments in wrong order in boost::math::tools::halley_iterate(first arg=%1%)There appears to be no root to be found in boost::math::tools::newton_raphson_iterate, perhaps we have a local minima near current best guess of %1%Root finding evaluation exceeded %1% iterations, giving up now.boost::math::erf_inv<%1%>multiplyColumns of m1Rows of m2stan/lib/stan_math/lib/eigen_3.3.9/Eigen/src/Core/Product.hlhs.cols() == rhs.rows() && "invalid matrix product" && "if you wanted a coeff-wise or a dot product use the respective explicit functions" (in 'prophet.stan', line 83, column 4 to column 28)no more scalars to readvector::_M_default_appendLower bounded variablelb_free (found before start of program) (in 'prophet.stan', line 37, column 4 to column 51) (in 'prophet.stan', line 42, column 6 to column 66) (in 'prophet.stan', line 33, column 11 to column 16) (in 'prophet.stan', line 32, column 11 to column 12)gammak_sS + 1stan/lib/stan_math/lib/eigen_3.3.9/Eigen/src/Core/CommaInitializer.h((m_row+m_currentBlockRows) == m_xpr.rows() || m_xpr.cols() == 0) && m_col == m_xpr.cols() && "Too few coefficients passed to comma initializer (operator<<)"assigning variable k_s((SizeAtCompileTime == Dynamic && (MaxSizeAtCompileTime==Dynamic || size<=MaxSizeAtCompileTime)) || SizeAtCompileTime == size) && size>=0startRow >= 0 && blockRows >= 0 && startRow <= xpr.rows() - blockRows && startCol >= 0 && blockCols >= 0 && startCol <= xpr.cols() - blockCols, expecting dimension = ; a function was called with arguments of different scalar, array, vector, or matrix types, and they were not consistently sized; all arguments must be scalars or multidimensional values of the same shape.has dimension = Vector of dependent variablesWeight vectorVector of interceptsScale vectorpositive finiteLocation parameterfiniteRandom variablenot nanScale parameterpositive, but has size ; and they must be the same size.has size = ] is stan/lib/stan_math/lib/eigen_3.3.9/Eigen/src/Core/Redux.hthis->rows()>0 && this->cols()>0 && "you are using an empty matrix"vector::_M_emplace_back_auxColumns of Rows of Badd (in 'prophet.stan', line 74, column 4 to column 65) (in 'prophet.stan', line 60, column 4 to column 53) (in 'prophet.stan', line 61, column 4 to column 70) (in 'prophet.stan', line 58, column 11 to column 12)assigning variable gammasubtractInterceptMatrix of independent variablesassigning variable trend (in 'prophet.stan', line 120, column 4 to column 54) (in 'prophet.stan', line 122, column 4 to column 64) (in 'prophet.stan', line 124, column 4 to column 29) (in 'prophet.stan', line 137, column 2 to line 142, column 4) (in 'prophet.stan', line 131, column 2 to column 19) (in 'prophet.stan', line 133, column 2 to column 29) (in 'prophet.stan', line 132, column 2 to column 37) (in 'prophet.stan', line 134, column 2 to column 27) (in 'prophet.stan', line 130, column 2 to column 19) (in 'prophet.stan', line 114, column 2 to column 17) (in 'prophet.stan', line 112, column 2 to column 18) (in 'prophet.stan', line 113, column 2 to column 26) (in 'prophet.stan', line 110, column 2 to column 9) (in 'prophet.stan', line 111, column 2 to column 9)stan/lib/stan_math/lib/eigen_3.3.9/Eigen/src/Core/Transpose.h(!check_transpose_aliasing_run_time_selector ::IsTransposed,OtherDerived> ::run(extract_data(dst), other)) && "aliasing detected during transposition, use transposeInPlace() " "or evaluate the rhs into a temporary using .eval()"4gamma_p<%1%>(%1%, %1%)normal_id_glm_lpdfnormal_lpdfdouble_exponential_lpdffloat_distance<%1%>(%1%, %1%)boost::math::tools::halley_iterate<%1%>boost::math::erfc_inv<%1%>(%1%, %1%)boost::math::erf_inv<%1%>(%1%, %1%)boost::math::powm1<%1%>(%1%, %1%)boost::math::log1pmx<%1%>(%1%)boost::math::gamma_p<%1%>(%1%, %1%) (in 'prophet.stan', line 118, column 2 to column 18) (in 'prophet.stan', line 123, column 35 to line 125, column 3) (in 'prophet.stan', line 123, column 9 to line 125, column 3) (in 'prophet.stan', line 121, column 35 to line 123, column 3) (in 'prophet.stan', line 121, column 9 to line 125, column 3) (in 'prophet.stan', line 119, column 28 to line 121, column 3) (in 'prophet.stan', line 119, column 2 to line 125, column 3) (in 'prophet.stan', line 9, column 11 to column 12) (in 'prophet.stan', line 9, column 14 to column 15) (in 'prophet.stan', line 9, column 4 to column 19) (in 'prophet.stan', line 10, column 15 to column 16) (in 'prophet.stan', line 10, column 4 to column 24) (in 'prophet.stan', line 11, column 4 to column 15) (in 'prophet.stan', line 14, column 4 to column 28) (in 'prophet.stan', line 15, column 4 to column 33) (in 'prophet.stan', line 16, column 4 to column 15) (in 'prophet.stan', line 21, column 8 to column 26) (in 'prophet.stan', line 22, column 8 to column 28) (in 'prophet.stan', line 20, column 58 to line 23, column 7) (in 'prophet.stan', line 20, column 6 to line 23, column 7) (in 'prophet.stan', line 24, column 6 to column 19) (in 'prophet.stan', line 19, column 19 to line 25, column 5) (in 'prophet.stan', line 19, column 4 to line 25, column 5) (in 'prophet.stan', line 26, column 4 to column 13) (in 'prophet.stan', line 7, column 73 to line 27, column 3) (in 'prophet.stan', line 32, column 4 to column 20) (in 'prophet.stan', line 33, column 4 to column 22) (in 'prophet.stan', line 34, column 4 to column 14) (in 'prophet.stan', line 40, column 4 to column 13) (in 'prophet.stan', line 43, column 6 to column 29) (in 'prophet.stan', line 41, column 19 to line 44, column 5) (in 'prophet.stan', line 41, column 4 to line 44, column 5) (in 'prophet.stan', line 45, column 4 to column 17) (in 'prophet.stan', line 31, column 78 to line 46, column 3) (in 'prophet.stan', line 58, column 4 to column 20) (in 'prophet.stan', line 57, column 4 to line 62, column 3) (in 'prophet.stan', line 73, column 4 to line 75, column 3) (in 'prophet.stan', line 82, column 4 to line 84, column 3) (08jL>.St11_Mutex_baseILN9__gnu_cxx12_Lock_policyE2EE[SM1s3e?-v?)? 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S?Cl?0AM5?q탫?l\?##_?ꂲ\?-BNS'?-@?&x?O2{?B%T?n ?ʝ(?ze?2?V5S?-YЊ!?Qܨ?]}?@9?5X?s\'??`H?T.?aYc?*ߺ3?wr?}k? $v?0w1s?aC?PS?Y$?<~ ?E?\X?.s*?&V?5[?Nk=?'o1Aq?,gC?ف?E?k?ă&?K?I?GH?XujvK? 2h]?O_ ?Zsxf?6|M=??{_?ģݥ}?R]ȗ?7"U?o`TY??+@?J?! ?n=?3&ڐ?p$p?<\I;?m?̷y8?zP?s*J"?[5?+M[Iֺ?A]X?N5boost16bad_lexical_castEX^ShN^SN4stan9callbacks6writerE[SNN7cmdstan8argumentE[SNN7cmdstan20categorical_argumentEX^SNNN7cmdstan15valued_argumentEX^S8NNN7cmdstan18singleton_argumentINSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEEEX^SpNXNN7cmdstan13arg_data_fileEX^SNNN7cmdstan8arg_dataEX^SN NN7cmdstan18singleton_argumentIiEEX^SHNXNN7cmdstan6arg_idEX^SNpNN7cmdstan8arg_initEX^SNNN7cmdstan19arg_diagnostic_fileEX^SNNN7cmdstan15arg_output_fileEX^S NNN7cmdstan19arg_output_sig_figsEX^SXNpNN7cmdstan16arg_profile_fileEX^SNNN7cmdstan11arg_refreshEX^SNpNN7cmdstan10arg_outputEX^SN 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F?+.O=q6^臉O: ׇ+{5cgtf?h?)q0 ?e>EaUUUUUU?AAp?q|?YYUUUUUU?^^^^^^ܿ?$@Y@@@@j@.AcAחAeA _BvH7BmB@0BļB4&k C7yAC؅W4vCNgmC=`XC@xDPKDMDJ-DyCxD(,* E52TEqىE/'E!1Eꌠ9Y>)F$_FnFF"F|FMraB3G yhGiWCG*GJH\)c=H7]rHaxHyֲHL}YI\CkFI3T|I\'Isȡ1I:~^Jd~QJvaJ0}GJ>nllJ$KAjZK=P1PKMZ>dKW`M}Kmn/LDcL^LpuLafirM?O8MrbnMG9Mz)M:Ft NdȋBN=ֺ.wN 9iNCNuOILLO֯OO[пOE!P/'%UP_QP6PbDP{U[*QmUx`Q*4VQz5߼QlX R.4R9mr"iRY) kRعeR$N(Sa򮌮>S }W-sSO\]ScbuSp] T%L9hGT.B}T}Ô%IT\nTsqUFQU`RUxӫU?+dpU5=%VN=@[Vҟ&VG0JV=:YVf$0W&sdWW)>W]3sMXk5!a9XBioX)8ӣX*4X5AHxY(-\CYr%4xYv/AYiY?ZOMZ20HwZ~$|7Z-[bZXC}"[;/V[ ;C-[SJ[= \[M"4+\0IΕ2a\|AH\[R\ysKp]WPM4]mH=j]Į]-f]u8W]am ^|M$D@^`-Ut^x^WUH^P.5_[ypH_r]~_':__ k_EW`RVR`'.N`(:W"`Yv5`o%&a.s\ax}?5ȑa\,C:a 4az]1beb"b _Sb72cϢER:ckpc2gFxc@BXVch)5,dtC7Ddx0REydVfYd6 6dCCuesTNNeGe1eeax~Ze= "f β̈Wf_jfbf8jfD},gJ#agZqg$gwWӈhה,5h :7ekhHDbhZսghJzg iN@iZbti: iDhTi VBijkzIjsYH j7-4j 8jL%k0V(wSkk21Ukjk*do^k5= 6~'l ]]l8l@4l7#l#s:V!2mOBɫfm㒻Tmp;5m Š±!nr-3;ngRJqn眥na}!n,}ovk*:Eobzo=$qE}om͖o\Ȁp9}UPpCD pT&)p4osp%#qVA1/XqkYqz42q܍qSr-rCbrnr1{Jr _|sNsv[06sTrlst"sRyXsW tquAtztUutGtc2 tXSTv/Ngvazjv}+vZ/v(wp-T_w&2bw~Ù:w\4@Iw!2xT):gx0xg^Jp5|x\By3tᮺvU0 5]JB-;eUkE=ƚpOܼw kAV<ЍU1(\Qӵɦqˋ#w"mSx@I̮Wζ]y<7VM6OH8oꖐ:%˅tφ* 45*g8;?Ȅ'DŖ%Οkb}$l_ Xf&ޓJ|l_bS04`U&N~)p$wߏ帟ߦ}t_ϛpDk11eU%ͬ{?;+*\Ӓsi$$d̈Po ̼,eX@bx x9?{Ηp\{2~h髤8E"&'O'1cȌ8eްeǃqB]X,iMpdJwmk}{x wyTś[[=]S5ȳ\*_F%94›\rξTSܷA"x\ӛ S!{Z:0ܵ△\S٨::CwiseBinaryOp(const Lhs&, const Rhs&, const BinaryOp&) [with BinaryOp = Eigen::internal::scalar_product_op; LhsType = const Eigen::Matrix; RhsType = const Eigen::Matrix; Eigen::CwiseBinaryOp::Lhs = Eigen::Matrix; Eigen::CwiseBinaryOp::Rhs = Eigen::Matrix]typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >; typename Eigen::internal::traits::Scalar = double]Eigen::CwiseBinaryOp::CwiseBinaryOp(const Lhs&, const Rhs&, const BinaryOp&) [with BinaryOp = Eigen::internal::scalar_quotient_op; LhsType = const Eigen::Matrix; RhsType = const Eigen::CwiseNullaryOp, const Eigen::Matrix >; Eigen::CwiseBinaryOp::Lhs = Eigen::Matrix; Eigen::CwiseBinaryOp::Rhs = Eigen::CwiseNullaryOp, const Eigen::Matrix >]Eigen::CwiseNullaryOp::CwiseNullaryOp(Eigen::Index, Eigen::Index, const NullaryOp&) [with NullaryOp = Eigen::internal::scalar_constant_op; PlainObjectType = const Eigen::Matrix; Eigen::Index = long int]Eigen::CwiseBinaryOp::CwiseBinaryOp(const Lhs&, const Rhs&, const BinaryOp&) [with BinaryOp = Eigen::internal::scalar_product_op; LhsType = const Eigen::CwiseNullaryOp, const Eigen::Matrix >; RhsType = const Eigen::Matrix; Eigen::CwiseBinaryOp::Lhs = Eigen::CwiseNullaryOp, const Eigen::Matrix >; Eigen::CwiseBinaryOp::Rhs = Eigen::Matrix]Eigen::CwiseNullaryOp::CwiseNullaryOp(Eigen::Index, Eigen::Index, const NullaryOp&) [with NullaryOp = Eigen::internal::scalar_constant_op; PlainObjectType = Eigen::Matrix; Eigen::Index = long int]Eigen::CwiseBinaryOp::CwiseBinaryOp(const Lhs&, const Rhs&, const BinaryOp&) [with BinaryOp = Eigen::internal::scalar_product_op; LhsType = const Eigen::CwiseNullaryOp, const Eigen::Matrix >; RhsType = const Eigen::Map, 0, Eigen::Stride<0, 0> >; Eigen::CwiseBinaryOp::Lhs = Eigen::CwiseNullaryOp, const Eigen::Matrix >; Eigen::CwiseBinaryOp::Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >]Eigen::MapBase::MapBase(Eigen::MapBase::PointerType, Eigen::Index, Eigen::Index) [with Derived = Eigen::Block, -1, 1, true>, -1, 1, false>; Eigen::MapBase::PointerType = double*; Eigen::Index = long int]Eigen::Block::Block(XprType&, Eigen::Index, Eigen::Index, Eigen::Index, Eigen::Index) [with XprType = Eigen::Block, -1, 1, true>; int BlockRows = -1; int BlockCols = 1; bool InnerPanel = false; Eigen::Index = long int]Eigen::CwiseNullaryOp::CwiseNullaryOp(Eigen::Index, Eigen::Index, const NullaryOp&) [with NullaryOp = Eigen::internal::scalar_constant_op; PlainObjectType = Eigen::Matrix; Eigen::Index = long int]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseNullaryOp, Eigen::Matrix >; Functor = Eigen::internal::div_assign_op]T* rapidjson::internal::Stack::PushUnsafe(std::size_t) [with T = char; Allocator = rapidjson::CrtAllocator; std::size_t = long unsigned int]void rapidjson::internal::BigInteger::PushBack(rapidjson::internal::BigInteger::Type)Eigen::CwiseNullaryOp::CwiseNullaryOp(Eigen::Index, Eigen::Index, const NullaryOp&) [with NullaryOp = Eigen::internal::scalar_constant_op; PlainObjectType = const Eigen::Matrix; Eigen::Index = long int]typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::Matrix; typename Eigen::internal::traits::Scalar = double]Eigen::DenseCoeffsBase::CoeffReturnType Eigen::DenseCoeffsBase::operator()(Eigen::Index, Eigen::Index) const [with Derived = Eigen::Matrix; Eigen::DenseCoeffsBase::CoeffReturnType = const double&; Eigen::Index = long int]void* Eigen::internal::aligned_malloc(std::size_t)void Eigen::PlainObjectBase::resize(Eigen::Index, Eigen::Index) [with Derived = Eigen::Matrix; Eigen::Index = long int]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; T1 = double; T2 = double]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseNullaryOp, Eigen::Matrix >; T1 = double; T2 = double]rapidjson::internal::BigInteger& rapidjson::internal::BigInteger::operator<<=(std::size_t)rapidjson::internal::DiyFp rapidjson::internal::DiyFp::Normalize() constrapidjson::internal::DiyFp rapidjson::internal::GetCachedPower10(int, int*)rapidjson::internal::DiyFp rapidjson::internal::GetCachedPowerByIndex(std::size_t)bool rapidjson::internal::StrtodDiyFp(const char*, int, int, double*)double rapidjson::internal::DiyFp::ToDouble() constdouble rapidjson::internal::StrtodBigInteger(double, const char*, int, int)rapidjson::internal::BigInteger::BigInteger(const char*, std::size_t)static uint64_t rapidjson::internal::BigInteger::ParseUint64(const char*, const char*)double rapidjson::internal::Double::NextPositiveDouble() constbool rapidjson::internal::BigInteger::Difference(const rapidjson::internal::BigInteger&, rapidjson::internal::BigInteger*) constdouble rapidjson::internal::StrtodFullPrecision(double, int, const char*, std::size_t, std::size_t, int)double rapidjson::internal::Pow10(int)??@@8@^@@@@&AKAAA2A(;L4BuwsBuwB7Bs6Ch0{CZAC Ƶ;(DlYaRwNDΤ5D{zhRlD!a?@)E~tE凗Egi=-FQ[F -n'F3 VF3 VIGAsb!G3xG]>H޲HH_Tt7IdaIp]IDh,6JHH Jh9/JLp8;K3KKA K$sPDL,xL;DL%{RMG#uMc:M)NZ3cN;N(I_O@5&yOaO#L4Pl]öP 'WP~ϸPQ2C3QJ4xRJ4xoR.h2R`>0S M1|SaS91KTTmTi3ZMUfyW{Uy>B/ULRBV3q VlF WĺL/nW С\dW̼Ws6X픐aXf>~YgY"𤽳Y=t3ZaZyy[r>g[>t0K U[aE6\R*Q\=ٴ]syQp]1"]đ}jA^_tک^Gc׍c_x b}_4(ȵ_;ϘfQ`ܕN0`@T&Vt%a#aGPÃap v[fbԒ Vb0{_>c,$ccCKld ؛8>d/GKZd?0[eϗe-5fH㴢f/-gq1Ov~g 2c$g!rAYh6h٩c_6i7,&ia(j+*^jzj?@Sbk k@Al@lcÀ "m8q.QmnUsnD}Rn#F)Uo.oU;A7p.џ9pMC2q&0}qUjk&r!S͟qr9D}Hɼr8 Vs~pso,MxxV&,)5y'wyU zKrJzގ=_] {Wrq{[v0{h~Gi|hx|;7;U})lgˈ}w,#]A/:Y0Y$u dA}1G RjA8,HxhfkpAWr4նOKvAUi%M&}AC<{:GkAo N ƉA]K`5rm[A0cd:<-pAL]1SO;{ݜAeaCGX9AÛ$]*AԔSJ'=AQ& !c|AWz+6CPAfv`0eQdkAtҦ7KA_CMkA;ǘA~Ӧ .r{AQ3Z@Y٧A]DEO'A1XFks4{86A2E/.Ap=@\gAmsZ bilBڻTRi@]9d B:܄#FCeiEWB~M9p<,h-PBSD1~ 5<B]ZX`e&B Z6.H- k%-B\gn3B:%a[ṢJ>:BiS%L1VABk[n#HBUxm%rĽNBZ]eP[ UBϏؖ0P||\B`%M+ʂXPcBZJJ{|Nj0N+jB҂? qBs7e DdwBT 3F~BQ zhY"B7CW!An}BZoNMb _ 8eB$kbRB63gPBB6kb5B[W{=,BCKFl 4%B&2._ : Ba4h8 S]Ba4h8 S]BnyxP:6 B,Zyg"%B?y T}+B ^W&C K[5B @.EqABx]3 mPBXmr}bB޵AJTyCaj6 C7nNi:$CBr\-,[WCg(Ik Cz@&\2e'Co&,~zCԇ;.CRx#`5CN_::Scalar& Eigen::DenseCoeffsBase::operator()(Eigen::Index, Eigen::Index) [with Derived = Eigen::Matrix; Eigen::DenseCoeffsBase::Scalar = double; Eigen::Index = long int]Eigen::DenseCoeffsBase::Scalar& Eigen::DenseCoeffsBase::operator()(Eigen::Index) [with Derived = Eigen::Matrix; Eigen::DenseCoeffsBase::Scalar = double; Eigen::Index = long int]Eigen::DenseCoeffsBase::Scalar& Eigen::DenseCoeffsBase::operator[](Eigen::Index) [with Derived = Eigen::Matrix; Eigen::DenseCoeffsBase::Scalar = double; Eigen::Index = long int]void Eigen::PlainObjectBase::resize(Eigen::Index, Eigen::Index) [with Derived = Eigen::Matrix; Eigen::Index = long int]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseNullaryOp, Eigen::Matrix >; T1 = double; T2 = double]Eigen::MapBase::MapBase(Eigen::MapBase::PointerType, Eigen::Index, Eigen::Index) [with Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >; Eigen::MapBase::PointerType = const double*; Eigen::Index = long int]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; T1 = double; T2 = double]void Eigen::PlainObjectBase::resize(Eigen::Index) [with Derived = Eigen::Matrix; Eigen::Index = long int]Eigen::CwiseNullaryOp::CwiseNullaryOp(Eigen::Index, Eigen::Index, const NullaryOp&) [with NullaryOp = Eigen::internal::scalar_identity_op; PlainObjectType = Eigen::Matrix; Eigen::Index = long int]Eigen::MapBase::MapBase(Eigen::MapBase::PointerType, Eigen::Index, Eigen::Index) [with Derived = Eigen::Block, -1, -1, false>; Eigen::MapBase::PointerType = double*; Eigen::Index = long int]Eigen::Block::Block(XprType&, Eigen::Index, Eigen::Index, Eigen::Index, Eigen::Index) [with XprType = Eigen::Matrix; int BlockRows = -1; int BlockCols = -1; bool InnerPanel = false; Eigen::Index = long int]typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]Eigen::CwiseBinaryOp::CwiseBinaryOp(const Lhs&, const Rhs&, const BinaryOp&) [with BinaryOp = Eigen::internal::scalar_product_op; LhsType = const Eigen::ArrayWrapper >; RhsType = const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >; Eigen::CwiseBinaryOp::Lhs = Eigen::ArrayWrapper >; Eigen::CwiseBinaryOp::Rhs = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >]Eigen::CwiseBinaryOp::CwiseBinaryOp(const Lhs&, const Rhs&, const BinaryOp&) [with BinaryOp = Eigen::internal::scalar_sum_op; LhsType = const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >; RhsType = const Eigen::ArrayWrapper >; Eigen::CwiseBinaryOp::Lhs = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >; Eigen::CwiseBinaryOp::Rhs = Eigen::ArrayWrapper >]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > >; T1 = double; T2 = double]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >; T1 = double; T2 = double]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseNullaryOp, Eigen::Matrix >; T1 = double; T2 = double]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >; T1 = double; T2 = double]typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Matrix; Derived = Eigen::Matrix; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double]typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]Eigen::CwiseBinaryOp::CwiseBinaryOp(const Lhs&, const Rhs&, const BinaryOp&) [with BinaryOp = Eigen::internal::scalar_sum_op; LhsType = const Eigen::Matrix; RhsType = const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Eigen::CwiseBinaryOp::Lhs = Eigen::Matrix; Eigen::CwiseBinaryOp::Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >; T1 = double; T2 = double]void rapidjson::GenericReader::ParseNumber(InputStream&, Handler&) [with unsigned int parseFlags = 274u; InputStream = rapidjson::BasicIStreamWrapper >; Handler = cmdstan::json::RapidJSONHandler; SourceEncoding = rapidjson::UTF8<>; TargetEncoding = rapidjson::UTF8<>; StackAllocator = rapidjson::CrtAllocator]T* rapidjson::internal::Stack::Pop(std::size_t) [with T = char; Allocator = rapidjson::CrtAllocator; std::size_t = long unsigned int]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::Matrix; Functor = Eigen::internal::add_assign_op]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::Matrix; Functor = Eigen::internal::add_assign_op]Eigen::MapBase::MapBase(Eigen::MapBase::PointerType, Eigen::Index, Eigen::Index) [with Derived = Eigen::Block, -1, 1, true>; Eigen::MapBase::PointerType = double*; Eigen::Index = long int]Eigen::Block::Block(XprType&, Eigen::Index) [with XprType = Eigen::Matrix; int BlockRows = -1; int BlockCols = 1; bool InnerPanel = true; Eigen::Index = long int]unsigned int rapidjson::GenericReader::ParseHex4(InputStream&, std::size_t) [with InputStream = rapidjson::BasicIStreamWrapper >; SourceEncoding = rapidjson::UTF8<>; TargetEncoding = rapidjson::UTF8<>; StackAllocator = rapidjson::CrtAllocator; std::size_t = long unsigned int]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; T1 = double; T2 = double]Eigen::CwiseBinaryOp::CwiseBinaryOp(const Lhs&, const Rhs&, const BinaryOp&) [with BinaryOp = Eigen::internal::scalar_difference_op; LhsType = const Eigen::Matrix; RhsType = const Eigen::Matrix; Eigen::CwiseBinaryOp::Lhs = Eigen::Matrix; Eigen::CwiseBinaryOp::Rhs = Eigen::Matrix]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >; Functor = Eigen::internal::add_assign_op]Eigen::CwiseBinaryOp::CwiseBinaryOp(const Lhs&, const Rhs&, const BinaryOp&) [with BinaryOp = Eigen::internal::scalar_product_op; LhsType = const Eigen::Matrix; RhsType = const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; Eigen::CwiseBinaryOp::Lhs = Eigen::Matrix; Eigen::CwiseBinaryOp::Rhs = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >; Functor = Eigen::internal::add_assign_op]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >; T1 = double; T2 = double]Eigen::CwiseBinaryOp::CwiseBinaryOp(const Lhs&, const Rhs&, const BinaryOp&) [with BinaryOp = Eigen::internal::scalar_sum_op; LhsType = const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; RhsType = const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > >; Eigen::CwiseBinaryOp::Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Eigen::CwiseBinaryOp::Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > >]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >; T1 = double; T2 = double]void Eigen::DenseBase::resize(Eigen::Index, Eigen::Index) [with Derived = Eigen::Block, -1, 1, true>; Eigen::Index = long int]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >; T1 = double; T2 = double]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseUnaryOp, const Eigen::Matrix >; T1 = double; T2 = double]void rapidjson::GenericReader::ParseString(InputStream&, Handler&, bool) [with unsigned int parseFlags = 274u; InputStream = rapidjson::BasicIStreamWrapper >; Handler = cmdstan::json::RapidJSONHandler; SourceEncoding = rapidjson::UTF8<>; TargetEncoding = rapidjson::UTF8<>; StackAllocator = rapidjson::CrtAllocator]void rapidjson::GenericReader::ParseStringToStream(InputStream&, OutputStream&) [with unsigned int parseFlags = 274u; SEncoding = rapidjson::UTF8<>; TEncoding = rapidjson::UTF8<>; InputStream = rapidjson::BasicIStreamWrapper >; OutputStream = rapidjson::GenericReader, rapidjson::UTF8<> >::StackStream; SourceEncoding = rapidjson::UTF8<>; TargetEncoding = rapidjson::UTF8<>; StackAllocator = rapidjson::CrtAllocator]static void rapidjson::UTF8::Encode(OutputStream&, unsigned int) [with OutputStream = rapidjson::GenericReader, rapidjson::UTF8<> >::StackStream; CharType = char]void rapidjson::GenericReader::ParseObject(InputStream&, Handler&) [with unsigned int parseFlags = 274u; InputStream = rapidjson::BasicIStreamWrapper >; Handler = cmdstan::json::RapidJSONHandler; SourceEncoding = rapidjson::UTF8<>; TargetEncoding = rapidjson::UTF8<>; StackAllocator = rapidjson::CrtAllocator]void rapidjson::GenericReader::ParseNull(InputStream&, Handler&) [with unsigned int parseFlags = 274u; InputStream = rapidjson::BasicIStreamWrapper >; Handler = cmdstan::json::RapidJSONHandler; SourceEncoding = rapidjson::UTF8<>; TargetEncoding = rapidjson::UTF8<>; StackAllocator = rapidjson::CrtAllocator]void rapidjson::GenericReader::ParseTrue(InputStream&, Handler&) [with unsigned int parseFlags = 274u; InputStream = rapidjson::BasicIStreamWrapper >; Handler = cmdstan::json::RapidJSONHandler; SourceEncoding = rapidjson::UTF8<>; TargetEncoding = rapidjson::UTF8<>; StackAllocator = rapidjson::CrtAllocator]void rapidjson::GenericReader::ParseFalse(InputStream&, Handler&) [with unsigned int parseFlags = 274u; InputStream = rapidjson::BasicIStreamWrapper >; Handler = cmdstan::json::RapidJSONHandler; SourceEncoding = rapidjson::UTF8<>; TargetEncoding = rapidjson::UTF8<>; StackAllocator = rapidjson::CrtAllocator]MPMPMPMPNP(NPXNPNPNPOP8OP`OPOPOPOPPP PPHPPvoid rapidjson::GenericReader::ParseArray(InputStream&, Handler&) [with unsigned int parseFlags = 274u; InputStream = rapidjson::BasicIStreamWrapper >; Handler = cmdstan::json::RapidJSONHandler; SourceEncoding = rapidjson::UTF8<>; TargetEncoding = rapidjson::UTF8<>; StackAllocator = rapidjson::CrtAllocator]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::Matrix; T1 = double; T2 = double]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::Matrix; T1 = double; T2 = double]void Eigen::PlainObjectBase::resize(Eigen::Index, Eigen::Index) [with Derived = Eigen::Matrix, -1, 1>; Eigen::Index = long int]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseUnaryView, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >; T1 = double; T2 = double]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; T1 = double; T2 = double]Eigen::MapBase::MapBase(Eigen::MapBase::PointerType, Eigen::Index) [with Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >; Eigen::MapBase::PointerType = double*; Eigen::Index = long int]Eigen::Product::Product(const Lhs&, const Rhs&) [with _Lhs = Eigen::Matrix; _Rhs = Eigen::Transpose >; int Option = 1; Eigen::Product::Lhs = Eigen::Matrix; Eigen::Product::Rhs = Eigen::Transpose >]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Transpose >, 1> >; T1 = double; T2 = double]Eigen::MapBase::MapBase(Eigen::MapBase::PointerType, Eigen::Index, Eigen::Index) [with Derived = Eigen::Block, 1, -1, false>; Eigen::MapBase::PointerType = const double*; Eigen::Index = long int]Eigen::Block::Block(XprType&, Eigen::Index) [with XprType = const Eigen::Matrix; int BlockRows = 1; int BlockCols = -1; bool InnerPanel = false; Eigen::Index = long int]Eigen::MapBase::MapBase(Eigen::MapBase::PointerType, Eigen::Index, Eigen::Index) [with Derived = Eigen::Block >, -1, 1, false>; Eigen::MapBase::PointerType = const double*; Eigen::Index = long int]Eigen::Block::Block(XprType&, Eigen::Index) [with XprType = const Eigen::Transpose >; int BlockRows = -1; int BlockCols = 1; bool InnerPanel = false; Eigen::Index = long int]Eigen::CwiseBinaryOp::CwiseBinaryOp(const Lhs&, const Rhs&, const BinaryOp&) [with BinaryOp = Eigen::internal::scalar_product_op; LhsType = const Eigen::Transpose, 1, -1, false> >; RhsType = const Eigen::Block >, -1, 1, false>; Eigen::CwiseBinaryOp::Lhs = Eigen::Transpose, 1, -1, false> >; Eigen::CwiseBinaryOp::Rhs = Eigen::Block >, -1, 1, false>]typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T1 = double; T2 = double]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, 1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Functor = Eigen::internal::add_assign_op]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Functor = Eigen::internal::sub_assign_op]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Functor = Eigen::internal::add_assign_op]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseNullaryOp, Eigen::Matrix >; Functor = Eigen::internal::mul_assign_op]Eigen::MapBase::MapBase(Eigen::MapBase::PointerType, Eigen::Index, Eigen::Index) [with Derived = Eigen::Block, -1, 1, true>; Eigen::MapBase::PointerType = double*; Eigen::Index = long int]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, 1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Functor = Eigen::internal::sub_assign_op]Eigen::CwiseBinaryOp::CwiseBinaryOp(const Lhs&, const Rhs&, const BinaryOp&) [with BinaryOp = Eigen::internal::scalar_product_op; LhsType = const Eigen::ArrayWrapper >; RhsType = const Eigen::ArrayWrapper >; Eigen::CwiseBinaryOp::Lhs = Eigen::ArrayWrapper >; Eigen::CwiseBinaryOp::Rhs = Eigen::ArrayWrapper >]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::ArrayWrapper >; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >; Functor = Eigen::internal::add_assign_op]Eigen::CwiseBinaryOp::CwiseBinaryOp(const Lhs&, const Rhs&, const BinaryOp&) [with BinaryOp = Eigen::internal::scalar_product_op; LhsType = const Eigen::ArrayWrapper >; RhsType = const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >; Eigen::CwiseBinaryOp::Lhs = Eigen::ArrayWrapper >; Eigen::CwiseBinaryOp::Rhs = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >]Eigen::CwiseNullaryOp::CwiseNullaryOp(Eigen::Index, Eigen::Index, const NullaryOp&) [with NullaryOp = Eigen::internal::scalar_constant_op; PlainObjectType = Eigen::Array; Eigen::Index = long int]Y@$@??{Gz?void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >; T1 = double; T2 = double]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::ArrayWrapper >; SrcXprType = Eigen::ArrayWrapper >; Functor = Eigen::internal::div_assign_op]Eigen::DenseCoeffsBase::CoeffReturnType Eigen::DenseCoeffsBase::operator()(Eigen::Index) const [with Derived = Eigen::Matrix; Eigen::DenseCoeffsBase::CoeffReturnType = const double&; Eigen::Index = long int]Eigen::MapBase::MapBase(Eigen::MapBase::PointerType, Eigen::Index, Eigen::Index) [with Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >; Eigen::MapBase::PointerType = double*; Eigen::Index = long int]Eigen::MapBase::MapBase(Eigen::MapBase::PointerType, Eigen::Index, Eigen::Index) [with Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >; Eigen::MapBase::PointerType = double*; Eigen::Index = long int]Eigen::Block::Block(XprType&, Eigen::Index) [with XprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; int BlockRows = -1; int BlockCols = 1; bool InnerPanel = true; Eigen::Index = long int]Eigen::MapBase::MapBase(Eigen::MapBase::PointerType, Eigen::Index, Eigen::Index) [with Derived = Eigen::Block, -1, 1, false>; Eigen::MapBase::PointerType = double*; Eigen::Index = long int]Eigen::Block::Block(XprType&, Eigen::Index, Eigen::Index, Eigen::Index, Eigen::Index) [with XprType = Eigen::Matrix; int BlockRows = -1; int BlockCols = 1; bool InnerPanel = false; Eigen::Index = long int]void Eigen::DenseBase::swap(const Eigen::DenseBase&) [with OtherDerived = Eigen::Block, -1, 1, true>; Derived = Eigen::Block, -1, 1, true>]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Transpose >; SrcXprType = Eigen::Block, 1, -1, false>; T1 = double; T2 = double]static void Eigen::internal::checkTransposeAliasing_impl::run(const Derived&, const OtherDerived&) [with Derived = Eigen::Transpose >; OtherDerived = Eigen::Block, 1, -1, false>; bool MightHaveTransposeAliasing = true]Eigen::internal::blas_data_mapper::blas_data_mapper(Scalar*, Index, Index) [with Scalar = double; Index = long int; int StorageOrder = 0; int AlignmentType = 0]static void Eigen::internal::selfadjoint_product_impl::run(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Block, -1, 1, false>; Lhs = Eigen::Block, -1, -1, false>; int LhsMode = 17; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Eigen::internal::selfadjoint_product_impl::Scalar = double]static Eigen::Index Eigen::internal::llt_inplace::unblocked(MatrixType&) [with MatrixType = Eigen::Matrix; Scalar = double; Eigen::Index = long int]Eigen::Block::Block(XprType&, Eigen::Index, Eigen::Index, Eigen::Index, Eigen::Index) [with XprType = Eigen::Matrix; int BlockRows = -1; int BlockCols = 1; bool InnerPanel = false; Eigen::Index = long int]Eigen::Block::Block(XprType&, Eigen::Index, Eigen::Index, Eigen::Index, Eigen::Index) [with XprType = Eigen::Matrix; int BlockRows = 1; int BlockCols = -1; bool InnerPanel = false; Eigen::Index = long int]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, 1, false>; SrcXprType = Eigen::CwiseNullaryOp, Eigen::Matrix >; Functor = Eigen::internal::div_assign_op]Eigen::Product::Product(const Lhs&, const Rhs&) [with _Lhs = Eigen::Matrix; _Rhs = Eigen::Matrix; int Option = 0; Eigen::Product::Lhs = Eigen::Matrix; Eigen::Product::Rhs = Eigen::Matrix]Eigen::CwiseBinaryOp::CwiseBinaryOp(const Lhs&, const Rhs&, const BinaryOp&) [with BinaryOp = Eigen::internal::scalar_sum_op; LhsType = const Eigen::Product, Eigen::Matrix, 0>; RhsType = const Eigen::Matrix; Eigen::CwiseBinaryOp::Lhs = Eigen::Product, Eigen::Matrix, 0>; Eigen::CwiseBinaryOp::Rhs = Eigen::Matrix]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, const Eigen::Matrix >; T1 = double; T2 = double]Eigen::Diagonal::Diagonal(MatrixType&, Eigen::Index) [with MatrixType = Eigen::Matrix; int _DiagIndex = 0; Eigen::Index = long int]Eigen::Diagonal::Diagonal(MatrixType&, Eigen::Index) [with MatrixType = const Eigen::Matrix; int _DiagIndex = 0; Eigen::Index = long int]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::ArrayWrapper, 0> >; SrcXprType = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > >; Functor = Eigen::internal::add_assign_op]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >; T1 = double; T2 = double]Eigen::CwiseNullaryOp::CwiseNullaryOp(Eigen::Index, Eigen::Index, const NullaryOp&) [with NullaryOp = Eigen::internal::scalar_constant_op; PlainObjectType = Eigen::Array; Eigen::Index = long int]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::ArrayWrapper >; SrcXprType = Eigen::ArrayWrapper >; Functor = Eigen::internal::div_assign_op]void Eigen::PlainObjectBase::resize(Eigen::Index, Eigen::Index) [with Derived = Eigen::Matrix; Eigen::Index = long int]void Eigen::internal::gemm_pack_rhs::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long int; DataMapper = Eigen::internal::const_blas_data_mapper; int nr = 4; bool Conjugate = false; bool PanelMode = true]void Eigen::internal::gemm_pack_lhs::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long int; DataMapper = Eigen::internal::blas_data_mapper; int Pack1 = 6; int Pack2 = 2; bool Conjugate = false; bool PanelMode = true]static Eigen::Index Eigen::internal::llt_inplace::blocked(MatrixType&) [with MatrixType = Eigen::Matrix; Scalar = double; Eigen::Index = long int]static Eigen::Index Eigen::internal::llt_inplace::unblocked(MatrixType&) [with MatrixType = Eigen::Block, -1, -1, false>; Scalar = double; Eigen::Index = long int]Eigen::Block::Block(XprType&, Eigen::Index, Eigen::Index, Eigen::Index, Eigen::Index) [with XprType = Eigen::Block, -1, -1, false>; int BlockRows = -1; int BlockCols = 1; bool InnerPanel = false; Eigen::Index = long int]Eigen::Block::Block(XprType&, Eigen::Index, Eigen::Index, Eigen::Index, Eigen::Index) [with XprType = Eigen::Block, -1, -1, false>; int BlockRows = 1; int BlockCols = -1; bool InnerPanel = false; Eigen::Index = long int]void Eigen::TriangularViewImpl<_MatrixType, _Mode, Eigen::Dense>::solveInPlace(const Eigen::MatrixBase&) const [with int Side = 2; OtherDerived = Eigen::Block, -1, -1, false>; _MatrixType = const Eigen::Transpose, -1, -1, false> >; unsigned int _Mode = 2u]Eigen::LLT& Eigen::LLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]Eigen::MapBase::MapBase(Eigen::MapBase::PointerType, Eigen::Index, Eigen::Index) [with Derived = Eigen::Block, 1, -1, false>; Eigen::MapBase::PointerType = double*; Eigen::Index = long int]Eigen::Block::Block(XprType&, Eigen::Index) [with XprType = Eigen::Matrix; int BlockRows = 1; int BlockCols = -1; bool InnerPanel = false; Eigen::Index = long int]Eigen::Block::Block(XprType&, Eigen::Index, Eigen::Index, Eigen::Index, Eigen::Index) [with XprType = Eigen::Block, 1, -1, false>; int BlockRows = 1; int BlockCols = -1; bool InnerPanel = false; Eigen::Index = long int]typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Block, 1, -1, false>, 1, -1, false> >; typename Eigen::internal::traits::Scalar = double]const EssentialVectorType Eigen::HouseholderSequence::essentialVector(Eigen::Index) const [with VectorsType = Eigen::Matrix; CoeffsType = Eigen::Matrix; int Side = 1; Eigen::HouseholderSequence::EssentialVectorType = Eigen::Block, -1, 1, false>; Eigen::Index = long int]Eigen::MapBase::MapBase(Eigen::MapBase::PointerType, Eigen::Index, Eigen::Index) [with Derived = Eigen::Block, -1, 1, false>; Eigen::MapBase::PointerType = const double*; Eigen::Index = long int]Eigen::Block::Block(XprType&, Eigen::Index, Eigen::Index, Eigen::Index, Eigen::Index) [with XprType = const Eigen::Matrix; int BlockRows = -1; int BlockCols = 1; bool InnerPanel = false; Eigen::Index = long int]Eigen::Stride::Stride(Eigen::Stride::Index, Eigen::Stride::Index) [with int _OuterStrideAtCompileTime = -1; int _InnerStrideAtCompileTime = 0; Eigen::Stride::Index = long int]Eigen::MapBase::MapBase(Eigen::MapBase::PointerType, Eigen::Index, Eigen::Index) [with Derived = Eigen::Map, 0, Eigen::OuterStride<> >; Eigen::MapBase::PointerType = const double*; Eigen::Index = long int]Eigen::Block::Block(XprType&, Eigen::Index) [with XprType = const Eigen::Map, 0, Eigen::OuterStride<> >; int BlockRows = 1; int BlockCols = -1; bool InnerPanel = true; Eigen::Index = long int]Eigen::Block::Block(XprType&, Eigen::Index, Eigen::Index, Eigen::Index, Eigen::Index) [with XprType = const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>; int BlockRows = 1; int BlockCols = -1; bool InnerPanel = false; Eigen::Index = long int]Eigen::DenseCoeffsBase::CoeffReturnType Eigen::DenseCoeffsBase::operator()(Eigen::Index, Eigen::Index) const [with Derived = Eigen::Map, 0, Eigen::OuterStride<> >; Eigen::DenseCoeffsBase::CoeffReturnType = double; Eigen::Index = long int]typename Eigen::LLT::Traits::MatrixU Eigen::LLT::matrixU() const [with _MatrixType = Eigen::Matrix; int _UpLo = 1; typename Eigen::LLT::Traits::MatrixU = const Eigen::TriangularView >, 2u>]void Eigen::TriangularViewImpl<_MatrixType, _Mode, Eigen::Dense>::solveInPlace(const Eigen::MatrixBase&) const [with int Side = 1; OtherDerived = Eigen::Matrix; _MatrixType = const Eigen::Transpose >; unsigned int _Mode = 2u]Eigen::Product::Product(const Lhs&, const Rhs&) [with _Lhs = Eigen::Matrix; _Rhs = Eigen::Matrix; int Option = 1; Eigen::Product::Lhs = Eigen::Matrix; Eigen::Product::Rhs = Eigen::Matrix]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::Product, Eigen::Matrix, 1>; T1 = double; T2 = double]Eigen::MapBase::MapBase(Eigen::MapBase::PointerType, Eigen::Index, Eigen::Index) [with Derived = Eigen::Block, -1, 1, true>; Eigen::MapBase::PointerType = const double*; Eigen::Index = long int]Eigen::Block::Block(XprType&, Eigen::Index) [with XprType = const Eigen::Matrix; int BlockRows = -1; int BlockCols = 1; bool InnerPanel = true; Eigen::Index = long int]Eigen::CwiseBinaryOp::CwiseBinaryOp(const Lhs&, const Rhs&, const BinaryOp&) [with BinaryOp = Eigen::internal::scalar_product_op; LhsType = const Eigen::Transpose, 1, -1, false> >; RhsType = const Eigen::Block, -1, 1, true>; Eigen::CwiseBinaryOp::Lhs = Eigen::Transpose, 1, -1, false> >; Eigen::CwiseBinaryOp::Rhs = Eigen::Block, -1, 1, true>]typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Matrix; Rhs = Eigen::Matrix; Eigen::internal::generic_product_impl::Scalar = double]Eigen::CwiseBinaryOp::CwiseBinaryOp(const Lhs&, const Rhs&, const BinaryOp&) [with BinaryOp = Eigen::internal::scalar_difference_op; LhsType = const Eigen::CwiseNullaryOp, Eigen::Matrix >; RhsType = const Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0>; Eigen::CwiseBinaryOp::Lhs = Eigen::CwiseNullaryOp, Eigen::Matrix >; Eigen::CwiseBinaryOp::Rhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0>]static void Eigen::internal::Assignment, Eigen::internal::sub_assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == DefaultProduct) || (Options == AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::sub_assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >; int Options = 0; Scalar = double; Eigen::internal::Assignment, Eigen::internal::sub_assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == DefaultProduct) || (Options == AliasFreeProduct))>::type>::SrcXprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0>]static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >; Eigen::internal::generic_product_impl::Scalar = double]static void Eigen::internal::Assignment, Eigen::internal::add_assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == DefaultProduct) || (Options == AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::add_assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >; int Options = 0; Scalar = double; Eigen::internal::Assignment, Eigen::internal::add_assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == DefaultProduct) || (Options == AliasFreeProduct))>::type>::SrcXprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0>]Eigen::Product::Product(const Lhs&, const Rhs&) [with _Lhs = Eigen::Matrix; _Rhs = Eigen::Matrix; int Option = 0; Eigen::Product::Lhs = Eigen::Matrix; Eigen::Product::Rhs = Eigen::Matrix]Eigen::Product::Product(const Lhs&, const Rhs&) [with _Lhs = Eigen::Product, Eigen::Matrix, 0>; _Rhs = Eigen::Transpose >; int Option = 0; Eigen::Product::Lhs = Eigen::Product, Eigen::Matrix, 0>; Eigen::Product::Rhs = Eigen::Transpose >]Eigen::Product::Product(const Lhs&, const Rhs&) [with _Lhs = Eigen::Product, Eigen::Matrix, 0>; _Rhs = Eigen::Transpose >; int Option = 1; Eigen::Product::Lhs = Eigen::Product, Eigen::Matrix, 0>; Eigen::Product::Rhs = Eigen::Transpose >]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 1>; T1 = double; T2 = double]Eigen::CwiseNullaryOp::CwiseNullaryOp(Eigen::Index, Eigen::Index, const NullaryOp&) [with NullaryOp = Eigen::internal::scalar_constant_op; PlainObjectType = Eigen::Matrix; Eigen::Index = long int]static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Product, Eigen::Matrix, 0>; Rhs = Eigen::Transpose >; Eigen::internal::generic_product_impl::Scalar = double]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::Matrix; T1 = double; T2 = double]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseUnaryOp, const Eigen::Product, Eigen::Matrix, 0> >; T1 = double; T2 = double]static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]Eigen::MapBase::MapBase(Eigen::MapBase::PointerType, Eigen::Index, Eigen::Index) [with Derived = Eigen::Block, 0>, -1, 1, false>; Eigen::MapBase::PointerType = double*; Eigen::Index = long int]Eigen::Block::Block(XprType&, Eigen::Index, Eigen::Index, Eigen::Index, Eigen::Index) [with XprType = Eigen::Diagonal, 0>; int BlockRows = -1; int BlockCols = 1; bool InnerPanel = false; Eigen::Index = long int]void Eigen::DenseBase::swap(const Eigen::DenseBase&) [with OtherDerived = Eigen::Block, -1, 1, true>, -1, 1, false>; Derived = Eigen::Block, -1, 1, true>, -1, 1, false>]Eigen::MapBase::MapBase(Eigen::MapBase::PointerType, Eigen::Index, Eigen::Index) [with Derived = Eigen::Block, -1, 1, false>; Eigen::MapBase::PointerType = double*; Eigen::Index = long int]Eigen::LDLT& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]void Eigen::PlainObjectBase::resize(Eigen::Index) [with Derived = Eigen::Matrix; Eigen::Index = long int]Eigen::ComputationInfo Eigen::LDLT::info() const [with _MatrixType = Eigen::Matrix; int _UpLo = 1]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; T1 = double; T2 = double]Eigen::MapBase::MapBase(Eigen::MapBase::PointerType, Eigen::Index, Eigen::Index) [with Derived = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>; Eigen::MapBase::PointerType = double*; Eigen::Index = long int]Eigen::Block::Block(XprType&, Eigen::Index) [with XprType = Eigen::Block, -1, -1, false>, -1, -1, false>; int BlockRows = -1; int BlockCols = 1; bool InnerPanel = true; Eigen::Index = long int]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Functor = Eigen::internal::sub_assign_op]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >; T1 = double; T2 = double]Eigen::MapBase::MapBase(Eigen::MapBase::PointerType, Eigen::Index, Eigen::Index) [with Derived = Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, true>; Eigen::MapBase::PointerType = double*; Eigen::Index = long int]Eigen::MapBase::MapBase(Eigen::MapBase::PointerType, Eigen::Index) [with Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >; Eigen::MapBase::PointerType = double*; Eigen::Index = long int]Eigen::MapBase::MapBase(Eigen::MapBase::PointerType, Eigen::Index, Eigen::Index) [with Derived = Eigen::Block, -1, -1, false>, -1, -1, false>; Eigen::MapBase::PointerType = double*; Eigen::Index = long int]Eigen::Block::Block(XprType&, Eigen::Index, Eigen::Index, Eigen::Index, Eigen::Index) [with XprType = Eigen::Block, -1, -1, false>; int BlockRows = -1; int BlockCols = -1; bool InnerPanel = false; Eigen::Index = long int]Eigen::Product::Product(const Lhs&, const Rhs&) [with _Lhs = Eigen::Transpose, -1, 1, false> >; _Rhs = Eigen::Block, -1, -1, false>, -1, -1, false>; int Option = 0; Eigen::Product::Lhs = Eigen::Transpose, -1, 1, false> >; Eigen::Product::Rhs = Eigen::Block, -1, -1, false>, -1, -1, false>]Eigen::MapBase::MapBase(Eigen::MapBase::PointerType, Eigen::Index, Eigen::Index) [with Derived = Eigen::Block, -1, -1, false>, 1, -1, false>; Eigen::MapBase::PointerType = double*; Eigen::Index = long int]Eigen::Block::Block(XprType&, Eigen::Index) [with XprType = Eigen::Block, -1, -1, false>; int BlockRows = 1; int BlockCols = -1; bool InnerPanel = false; Eigen::Index = long int]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::Block, -1, -1, false>, 1, -1, false>; Functor = Eigen::internal::add_assign_op]static void Eigen::internal::Assignment, Eigen::internal::sub_assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == DefaultProduct) || (Options == AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::sub_assign_op&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, false>; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >; Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; int Options = 0; Scalar = double; Eigen::internal::Assignment, Eigen::internal::sub_assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == DefaultProduct) || (Options == AliasFreeProduct))>::type>::SrcXprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>]Eigen::MapBase::MapBase(Eigen::MapBase::PointerType, Eigen::Index, Eigen::Index) [with Derived = Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>; Eigen::MapBase::PointerType = const double*; Eigen::Index = long int]Eigen::Block::Block(XprType&, Eigen::Index, Eigen::Index, Eigen::Index, Eigen::Index) [with XprType = const Eigen::Block, -1, 1, true>, -1, 1, false>; int BlockRows = -1; int BlockCols = 1; bool InnerPanel = false; Eigen::Index = long int]void Eigen::DenseBase::resize(Eigen::Index, Eigen::Index) [with Derived = Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>; Eigen::Index = long int]Eigen::MapBase::MapBase(Eigen::MapBase::PointerType, Eigen::Index, Eigen::Index) [with Derived = Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>; Eigen::MapBase::PointerType = double*; Eigen::Index = long int]Eigen::Block::Block(XprType&, Eigen::Index, Eigen::Index, Eigen::Index, Eigen::Index) [with XprType = Eigen::Block, -1, 1, true>, -1, 1, false>; int BlockRows = -1; int BlockCols = 1; bool InnerPanel = false; Eigen::Index = long int]void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]Eigen::Product::Product(const Lhs&, const Rhs&) [with _Lhs = Eigen::SelfAdjointView, -1, -1, false>, 1u>; _Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; int Option = 0; Eigen::Product::Lhs = Eigen::SelfAdjointView, -1, -1, false>, 1u>; Eigen::Product::Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >]void Eigen::DenseBase::resize(Eigen::Index, Eigen::Index) [with Derived = Eigen::Block, -1, 1, false>; Eigen::Index = long int]typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, 1, true>, -1, 1, false>; Derived = Eigen::Block, -1, 1, false>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double]typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Functor = Eigen::internal::add_assign_op]Eigen::Block::Block(XprType&, Eigen::Index, Eigen::Index, Eigen::Index, Eigen::Index) [with XprType = const Eigen::Block, -1, 1, false>; int BlockRows = -1; int BlockCols = 1; bool InnerPanel = false; Eigen::Index = long int]Eigen::Product::Product(const Lhs&, const Rhs&) [with _Lhs = Eigen::Block, -1, -1, false>, -1, -1, false>; _Rhs = Eigen::Block, -1, 1, false>; int Option = 0; Eigen::Product::Lhs = Eigen::Block, -1, -1, false>, -1, -1, false>; Eigen::Product::Rhs = Eigen::Block, -1, 1, false>]void Eigen::DenseBase::resize(Eigen::Index, Eigen::Index) [with Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >; Eigen::Index = long int]Eigen::MapBase::MapBase(Eigen::MapBase::PointerType, Eigen::Index, Eigen::Index) [with Derived = Eigen::Block, -1, -1, false>, -1, 1, true>; Eigen::MapBase::PointerType = double*; Eigen::Index = long int]Eigen::Block::Block(XprType&, Eigen::Index) [with XprType = Eigen::Block, -1, -1, false>; int BlockRows = -1; int BlockCols = 1; bool InnerPanel = true; Eigen::Index = long int]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::Block, -1, -1, false>, -1, 1, true>; Functor = Eigen::internal::add_assign_op]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, 1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Functor = Eigen::internal::sub_assign_op]static void Eigen::internal::Assignment, Eigen::internal::sub_assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == DefaultProduct) || (Options == AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::sub_assign_op&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, false>; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Transpose, -1, 1, false> >; int Options = 0; Scalar = double; Eigen::internal::Assignment, Eigen::internal::sub_assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == DefaultProduct) || (Options == AliasFreeProduct))>::type>::SrcXprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1, false> >, 0>]void Eigen::DenseBase::resize(Eigen::Index, Eigen::Index) [with Derived = Eigen::Block, -1, 1, true>, -1, 1, false>; Eigen::Index = long int]void Eigen::DenseBase::resize(Eigen::Index, Eigen::Index) [with Derived = Eigen::Diagonal, 0>; Eigen::Index = long int]Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::Diagonal, 0>; T1 = double; T2 = double]Eigen::Diagonal::Diagonal(MatrixType&, Eigen::Index) [with MatrixType = Eigen::Matrix; int _DiagIndex = -1; Eigen::Index = long int]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::Diagonal, -1>; T1 = double; T2 = double]static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::HouseholderSequence, Eigen::Matrix, 1>; Functor = Eigen::internal::assign_op; Weak = void; typename SrcXprType::Scalar = double; typename DstXprType::Scalar = double]const EigenvectorsType& Eigen::SelfAdjointEigenSolver<_MatrixType>::eigenvectors() const [with _MatrixType = Eigen::Matrix; Eigen::SelfAdjointEigenSolver<_MatrixType>::EigenvectorsType = Eigen::Matrix; typename _MatrixType::Scalar = double]const RealVectorType& Eigen::SelfAdjointEigenSolver<_MatrixType>::eigenvalues() const [with _MatrixType = Eigen::Matrix; Eigen::SelfAdjointEigenSolver<_MatrixType>::RealVectorType = Eigen::Matrix]Eigen::Product::Product(const Lhs&, const Rhs&) [with _Lhs = Eigen::Transpose >; _Rhs = Eigen::Matrix; int Option = 0; Eigen::Product::Lhs = Eigen::Transpose >; Eigen::Product::Rhs = Eigen::Matrix]Eigen::DenseCoeffsBase::Scalar& Eigen::DenseCoeffsBase::operator()(Eigen::Index) [with Derived = Eigen::Matrix; Eigen::DenseCoeffsBase::Scalar = double; Eigen::Index = long int]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Transpose >; SrcXprType = Eigen::Transpose >; T1 = double; T2 = double]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; T1 = double; T2 = double]Eigen::CwiseBinaryOp::CwiseBinaryOp(const Lhs&, const Rhs&, const BinaryOp&) [with BinaryOp = Eigen::internal::scalar_sum_op; LhsType = const Eigen::Matrix; RhsType = const Eigen::Matrix; Eigen::CwiseBinaryOp::Lhs = Eigen::Matrix; Eigen::CwiseBinaryOp::Rhs = Eigen::Matrix]Eigen::MapBase::MapBase(Eigen::MapBase::PointerType, Eigen::Index, Eigen::Index) [with Derived = Eigen::Block >, -1, 1, true>; Eigen::MapBase::PointerType = double*; Eigen::Index = long int]Eigen::CwiseNullaryOp::CwiseNullaryOp(Eigen::Index, Eigen::Index, const NullaryOp&) [with NullaryOp = Eigen::internal::scalar_constant_op; PlainObjectType = const Eigen::Matrix; Eigen::Index = long int]Eigen::Product::Product(const Lhs&, const Rhs&) [with _Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >; _Rhs = Eigen::Matrix; int Option = 0; Eigen::Product::Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >; Eigen::Product::Rhs = Eigen::Matrix]Eigen::Product::Product(const Lhs&, const Rhs&) [with _Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; _Rhs = Eigen::Matrix; int Option = 0; Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Eigen::Product::Rhs = Eigen::Matrix]void Eigen::internal::resize_if_allowed(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::Block, -1, -1, false>; T1 = double; T2 = double]bad lexical cast: source type value could not be interpreted as targetgoodbadvector::_M_range_check: __n (which is %zu) >= this->size() (which is %zu)Adaptation terminatedlib/rapidjson_1.1.0/rapidjson/internal/stack.hstackTop_static_cast(sizeof(T) * count) <= (stackEnd_ - stackTop_)empty_nested() must be true before calling recover_memory()lib/rapidjson_1.1.0/rapidjson/internal/biginteger.hcount_ < kCapacity,stan/lib/stan_math/lib/eigen_3.3.9/Eigen/src/Core/DenseCoeffsBase.hrow >= 0 && row < rows() && col >= 0 && col < cols()basic_string::substrlist elementSTAN_THREADS=falseSTAN_MPI=falseSTAN_OPENCL=falseSTAN_NO_RANGE_CHECKS=falseSTAN_CPP_OPTIMS=falsecount_ + offset <= kCapacitylib/rapidjson_1.1.0/rapidjson/internal/diyfp.hf != 0exp >= -348index < 87lib/rapidjson_1.1.0/rapidjson/internal/strtod.hadjustment >= 1 && adjustment < 8f <= kDpHiddenBit + kDpSignificandMaskdLen >= 0length > 0*p >= '0' && *p <= '9'lib/rapidjson_1.1.0/rapidjson/internal/ieee754.h!Sign()cmp != 0d >= 0.0length >= 1lib/rapidjson_1.1.0/rapidjson/internal/pow10.hn >= 0 && n <= 308length <= 0x7ffffffflength >= decimalPositionlength - decimalPosition <= 0x7fffffffexp >= (-0x7fffffff - 1) + dExpAdjustdExp <= 0x7fffffff - dLenname,thread_id,total_time,forward_time,reverse_time,chain_stack,no_chain_stack,autodiff_calls,no_autodiff_callsthread::id of a non-executing thread------------------------------------------------------------EXPERIMENTAL ALGORITHM: This procedure has not been thoroughly tested and may be unstable or buggy. The interface is subject to change.variance%uValid subarguments:variable: , error: non-rectangular array, error: nested objects not allowed, unexpected error, error: null values not allowed, error: boolean values not allowedstart_datetime = UTC Elapsed Time: seconds (Warm-up) seconds (Sampling) seconds (Total)Elements of inverse mass matrix:Diagonal elements of inverse mass matrix:index >= 0 && index < size()helphelp-all is not a valid value for "Valid values: (Default)=<Defaults to Usage: ... ... ... Begin by selecting amongst the following inference methods and diagnostics,Or see help information withPrints helpPrints entire argument treeAdditional configuration available by specifyingSee [ help | help-all ] for details on individual arguments.AllstringinitInitialization method: "x" initializes randomly between [-x, x], "0" initializes to 0, anything else identifies a file of values"2"2../src/test/test-models/test_model.init.RDay of month value is out of range 1..31Day of month is not valid for yearbooleanunsigned intstan_version_major = stan_version_minor = stan_version_patch = model = WARNING: No estimation is performed for num_warmup < 20WARNING: There aren't enough warmup iterations to fit the configured. three stages of adaptation as currently Reducing each adaptation stage to 15%/75%/10% of the given number of warmup iterations: init_buffer = adapt_window = term_buffer = is not a valid value for ; dimension size expression = must have a positive size, but is stan_version_majorstan_version_minorstan_version_patchnum_samplesnum_warmupsave_warmupthinappend_samplesalgorithmenginemax_depth(Warm-up) seconds(Sampling)Error: expected columns, but found instead for row covarianceread dense inv metricinv_metricrows * columnsvector sizeCannot get inverse metric from input file.Caught exception: Initialization failurevector::reservefailDummy argument to induce failures for testingFile output optionsOutput filePath to existing fileoutput.csvdiagnostic_fileAuxiliary output file for diagnostic information""refreshNumber of interations between screen updates0 <= refresh100sig_figsThe number of significant figures used for the output CSV files.0 <= integer <= 18 or -1 to use the default number of significant figures-1profile_fileFile to store profiling informationValid path and write acces to the folderprofile.csvadaptWarmup AdaptationengagedAdaptation engaged?[0, 1]Adaptation regularization scale0 < gamma0.05Adaptation target acceptance statistic0 < delta < 10.8kappaAdaptation relaxation exponent0 < kappa0.75t0Adaptation iteration offset0 < t010init_bufferWidth of initial fast adaptation interval75term_bufferWidth of final fast adaptation interval50windowInitial width of slow adaptation interval25hmcHamiltonian Monte CarloEngine for Hamiltonian Monte CarlostaticStatic integration timeint_timeTotal integration time for Hamiltonian evolution0 < int_time2 * pinutsThe No-U-Turn SamplerMaximum tree depth0 < max_depthGeometry of base manifoldunit_eEuclidean manifold with unit metricdiag_eEuclidean manifold with diag metricdense_eEuclidean manifold with dense metricmetric_fileInput file with precomputed Euclidean metricstepsizeStep size for discrete evolution0 < stepsizestepsize_jitterUniformly random jitter of the stepsize, in percent0 <= stepsize_jitter <= 1sampleBayesian inference with Markov Chain Monte CarloNumber of sampling iterations0 <= num_samples1000Number of warmup iterations0 <= warmupStream warmup samples to output?Period between saved samples0 < thinSampling algorithmfixed_paramFixed Parameter Samplernum_chainsNumber of chainsnum_chains > 0Year is out of valid range: 1400..9999Month number is out of range 1..12vector::_M_insert_auxempty_nested() must be false before calling recover_memory_nested()is not lower triangular;]=log1pvalue beyond numeric rangeis not symmetric. ] = Successful step completedConvergence detected: absolute change in objective function was below toleranceConvergence detected: relative change in objective function was below toleranceConvergence detected: gradient norm is below toleranceConvergence detected: relative gradient magnitude is below toleranceConvergence detected: absolute parameter change was below toleranceMaximum number of iterations hit, may not be at an optimaLine search failed to achieve a sufficient decrease, no more progress can be madeUnknown termination codenaninfinity%.*g0 <= tolbfgsBFGS with linesearchinit_alphaLine search step size for first iteration0 < init_alpha0.001Convergence tolerance on absolute changes in objective function valuetol_objConvergence tolerance on relative changes in objective function valuetol_rel_objConvergence tolerance on the norm of the gradienttol_gradConvergence tolerance on the relative norm of the gradienttol_rel_gradConvergence tolerance on changes in parameter valuetol_paramexpecting JSON object, found array, error: non-scalar array value-Inf-InfinityInfInfinityNaN, error: string values not allowedTotal number of iterationsStarting iterationFinal iterationRefresh rateIteration: / [%] (Adaptation)read diag inv metricvector_dCannot get inverse Euclidean metric from input file.check_finitecheck_positiveInverse Euclidean metric not positive definite.Input vectorDimension of mean vectorDimension of input vectorDimension of log std vectorMean vectorLog std vectorDimension of current vectorExpecting a square matrix; rows of Cholesky factorcolumns of Dimension of Cholesky factor, but must be less than or equal to attempt to redefine variable: vector::_M_insert_auxstan/lib/stan_math/lib/eigen_3.3.9/Eigen/src/Core/Dot.hsize() == other.size()Error evaluating model log probability: Non-finite gradient.Error evaluating model log probability: Non-finite function evaluation. Log probability=param idxfinite differrorStep size = expecting start of object ({) or array ([)lib/rapidjson_1.1.0/rapidjson/reader.h!HasParseError()GetSize() >= count * sizeof(T)Dimension of lhsDimension of rhs=stepsize__int_time__energy__treedepth__n_leapfrog__divergent__lp__accept_stat__p_g_vector::_M_fill_insertvariationalVariational inferenceVariational inference algorithmmeanfieldmean-field approximationfullrankfull-rank covarianceiterMaximum number of ADVI iterations.0 < iterNumber of Monte Carlo draws for computing the gradient.grad_samples0 < num_samplesNumber of Monte Carlo draws for estimate of ELBO.elbo_samplesetaStepsize scaling parameter.0 < etaEta Adaptation for Variational InferenceBoolean flag for eta adaptation.Number of iterations for eta adaptation.Relative tolerance parameter for convergence.Number of iterations between ELBO evaluationseval_elbo0 < eval_elboNumber of approximate posterior output draws to save.output_samples0 < output_samplesmethodAnalysis method (Note that method= is optional)optimizePoint estimationOptimization algorithmlbfgsLBFGS with linesearchhistory_sizeAmount of history to keep for L-BFGS0 < history_size5newtonNewton's method2000save_iterationsStream optimization progress to output?diagnoseModel diagnosticstestDiagnostic testgradientCheck model gradient against finite differencesepsilonFinite difference step size0 < epsilon1e-6Error threshold0 < errorgenerate_quantitiesGenerate quantities of interestfitted_paramsInput file of sample of fitted parameter values for model conditioned on dataNumerical overflow in metric adaptation. This occurs when the sampler encounters extreme values on the unconstrained space; this may happen when the posterior density function is too wide or improper. There may be problems with your model specification.vector::_M_range_insertChain [] (Warmup)Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.s.Peek() == '\"'lib/rapidjson_1.1.0/rapidjson/encodings.hcodepoint <= 0x10FFFFis.Peek() == '{'Unknown error.Error in JSON parsing at offset is.Peek() == '[' beyond array dimension range beyond int rangeinityintegerDimstructuredata syntax error),.Dim=c())inv_metric <- structure(c(.json.Rfile ending of is not supported by cmdstanRejecting initial value: Log probability evaluates to log(0), i.e. negative infinity. Stan can't start sampling from this initial value. Gradient evaluated at the initial value is not finite.Gradient evaluation took 1000 transitions using 10 leapfrog steps per transition would take seconds.Adjust your expectations accordingly!Initialization between (-) failed after attempts. Try specifying initial values, reducing ranges of constrained values, or reparameterizing the model.Initialization failed. Error evaluating the log probability at the initial value.Unrecoverable error evaluating the log probability at the initial value.Error evaluating initial BFGS point.circular_bufferInitial log joint probability = LS failed, Hessian resetOptimization terminated normally: Optimization terminated with error: Iter log prob ||dx|| ||grad|| alpha alpha0 # evals Notes Posterior is improper. Please check your model.No acceptably small step size could be found. Perhaps the posterior is not continuous?Exception initializing step size.log_prob). Your model may be either severely ill-conditioned or misspecified.has reached its maximum amount (The number of dropped evaluationsDimension of elbo_gradDimension of variational qDimension of variables in modelGradient of muNumber of adaptation iterationsBegin eta adaptation.Success! Found best value [eta = earlier than expected.].failed. Your model may be either severely ill-conditioned or misspecified.All proposed step-sizesCannot compute ELBO using the initial variational distribution.iter,time_in_seconds,ELBOStepsize adaptation complete.eta = Eta stepsizeRelative objective function toleranceMaximum iterationsBegin stochastic gradient ascent. iter ELBO delta_ELBO_mean delta_ELBO_med notes MEAN ELBO CONVERGED MEDIAN ELBO CONVERGED MAY BE DIVERGING... INSPECT ELBOThis variational approximation may not have converged to a good optimum.Informational Message: The maximum number of iterations is reached! The algorithm may not have converged.This variational approximation is not guaranteed to be meaningful.Drawing a sample of size from the approximate posterior... COMPLETED.Informational Message: The ELBO at a previous iteration is larger than the ELBO upon convergence!log_p__log_g__Number of Monte Carlo samples for gradientsNumber of Monte Carlo samples for ELBOEvaluate ELBO at every eval_elbo iterationNumber of posterior samples for outputrows()==other.rows() && cols()==other.cols()Empty set of draws from fitted model.Model doesn't generate any quantities of interest.Wrong number of parameter values in draws from fitted model. Expecting columns, found columns.array_var_contextvalidate_dimsstan/lib/stan_math/lib/eigen_3.3.9/Eigen/src/Core/util/BlasUtil.hincr==1Can't open specified file, "Found: "" but user specied files must end in .json or .R" and base file "Searching for "Can't open either of specified files," but cannot open "Found stan/lib/stan_math/lib/eigen_3.3.9/Eigen/src/Core/products/SelfadjointMatrixVector.hdest.rows()==a_lhs.rows() && dest.cols()==a_rhs.cols()stan/lib/stan_math/lib/eigen_3.3.9/Eigen/src/Cholesky/LLT.hmat.rows()==mat.cols()stan/lib/stan_math/lib/eigen_3.3.9/Eigen/src/Core/Diagonal.ha_index <= m_matrix.cols() && -a_index <= m_matrix.rows()stan/lib/stan_math/lib/eigen_3.3.9/Eigen/src/Core/products/GeneralBlockPanelKernel.h((!PanelMode) && stride==0 && offset==0) || (PanelMode && stride>=depth && offset<=stride)m.rows()==m.cols()stan/lib/stan_math/lib/eigen_3.3.9/Eigen/src/Core/SolveTriangular.hderived().cols() == derived().rows() && ((Side==OnTheLeft && derived().cols() == other.rows()) || (Side==OnTheRight && derived().cols() == other.cols()))a.rows()==a.cols()stan/lib/stan_math/lib/eigen_3.3.9/Eigen/src/Householder/HouseholderSequence.hk >= 0 && k < m_lengthstan/lib/stan_math/lib/eigen_3.3.9/Eigen/src/Core/Stride.hinnerStride>=0 && outerStride>=0m_isInitialized && "LLT is not initialized."stan/lib/stan_math/lib/eigen_3.3.9/Eigen/src/Core/products/GeneralMatrixMatrix.hdst.rows()==a_lhs.rows() && dst.cols()==a_rhs.cols()stan/lib/stan_math/lib/eigen_3.3.9/Eigen/src/Core/ProductEvaluators.hstan/lib/stan_math/lib/eigen_3.3.9/Eigen/src/Cholesky/LDLT.hm_isInitialized && "LDLT is not initialized."is not positive definite.check_pos_definitestan/lib/stan_math/lib/eigen_3.3.9/Eigen/src/Eigenvalues/Tridiagonalization.hn==matA.cols()n==hCoeffs.size()+1 || n==1stan/lib/stan_math/lib/eigen_3.3.9/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.hmatrix.cols() == matrix.rows()(options&~(EigVecMask|GenEigMask))==0 && (options&EigVecMask)!=EigVecMask && "invalid option parameter"mat.cols()==mat.rows() && diag.size()==mat.rows() && subdiag.size()==mat.rows()-1m_isInitialized && "SelfAdjointEigenSolver is not initialized."m_eigenvectorsOk && "The eigenvectors have not been computed together with the eigenvalues."Iteration Log joint probability = . Improved by Unique process identifierid >= 0dataInput data optionsInput data filerandomRandom number configurationRandom number generator seednon-negative integer < 4294967296 or -1 to generate seed from system timecould not convert calendar time to UTC timenum_threadsNumber of threads available to the program. For full effect, the model must be compiled with STAN_THREADS=true.num_threads == 11 or the value of the STAN_NUM_THREADS environment variable if set.info is either mistyped or misplaced.openclRe-compile the model with STAN_OPENCL to use OpenCL CmdStan arguments.Perhaps you meant one of the following valid configurations?A method must be specified!Failed to parse command arguments, cannot run model.Argument 'num_chains' can currently only be used for NUTS with adaptation and dense_e or diag_e metricArgument 'num_chains' can currently only be used for HMC with adaptation engagedFilename conflict, fitted_params file and output file have same name, must be different.File output name must not be blank# Missing fitted_params argument, cannot run generate_quantities without fitted sample.Error reading fitted param names from sample csv file "Mismatch between model and fitted_parameters csv file "TEST GRADIENT MODEModel contains no parameters, running fixed_param sampler, no updates to Markov chainArgument 'num_chains' can currently only be used for HMC with adaptation engaged. This model has no parameters, which currently means only the fixed_param algorithm can be usedThe number of warmup samples (num_warmup) must be greater than zero if adaptation is enabled.method=30No error.The document is empty.The document root must not be followed by other values.Invalid value.Missing a name for object member.Missing a colon after a name of object member.Missing a comma or '}' after an object member.Missing a comma or ']' after an array element or found a zero padded number.Incorrect hex digit after \u escape in string.The surrogate pair in string is invalid.Invalid escape character in string.Missing a closing quotation mark in string.Invalid encoding in string.Number too big to be stored in double.Missing fraction part in number.Missing exponent in number.Terminate parsing due to Handler error.Unspecific syntax error.stan::variational::normal_meanfield::calc_gradstan::variational::normal_fullrank::calc_gradstan::variational::advi::calc_ELBO_gradstan::variational::advi::calc_ELBOstan::variational::advi::stochastic_gradient_ascentstan::variational::advi::adapt_etastan::variational::advito_matrix(array)stan::variational::normal_meanfield::transformstan::variational::normal_meanfield::operator/=stan::variational::normal_meanfield::operator+=stan::variational::normal_meanfield::operator=stan::variational::normal_meanfield::set_omegastan::variational::normal_meanfield::set_mustan::variational::normal_meanfieldstan::variational::normal_fullrank::transformstan::variational::normal_fullrank::operator/=stan::variational::normal_fullrank::operator+=stan::variational::normal_fullrank::operator=stan::variational::set_L_cholstan::variational::set_mustan::variational::normal_fullrankstan::variational::print_progress;,0(H8(h8(P9$)p9P)9|)9)Q)W*A0*BX+F@,`F(-I.K.K8/L/hL/L0LX0M3@O4P_6_d6b7cD98c:hc$X@>`X>>>0 ?h?P?@@@ȫAЬHAЭAЮAx0BPhBȱB@BH(CXChCCDȹHDDxDPD EXEE(EhE0FFGhPGGGH`PHHH(H8HxHI(III @JhJXKpK0L0LL 8M0 hMx MX M0NN(NOXhOOXO 0P$pP$P*Q.`Q(/xQ0Q3R3(R4PR@8R9R9RCSE(S`F`S0HSISPSR T`T`TpVT _TUUU@(V`VVxVHWHpW0W@W@XhXX`XX0YhYYпYZpHZZZZ0[`[[p\ \\ ]"@]@+]3];(^Kp^@M^P^pQ^Q _0S_T_xT_U `UH``]`^` `a0`8a``a`xa`a`a0bad0bPgbj(dkpd`md0o ere0yez0ff8HggP(hЖph@ipii j؞hjPjСjk@Xk kPk0lllhm8mH0nnn8o@oo` pPpppx@qqqHr8r s@psPst t"pt"tH)tP)t/Hu/`u5u7u@>Hv>xvHEvEvhLHwLxwxSwSw[8x ]x0_x`yhe@ysyyyyzXzzz`z8{xh{{|8||ب||}(`}}H}X}h}`Pؘ(8x( (ȜPX XxPء(P0`PX`xxhhh8 P0xPp h !X&p+`1= xE XH!]PX~Xp~h~p~x~~~0H `0x@Px 8Ph 0Ȁ@P`p(@XpЁ  ( 00 H8 `@ xH P X ` ؂h p x 8 P h Ѓ   0 H( `8 x x  XX ` h p ؅x  8 P h Ȇ 0P(`@XpЇ0X (@HȈ`hp@8`x0؉8HP `8hPxhȊ(@h8Xx0X X 0Pp ((0@8X@pHPX`Ўhpx0XȏP`0Hp (0P 8P@hHȒ8Px 8 Гp ( @ XP!X!`!!!!"H#x$$$ؕ$$%@ %XP%X%%%ؖ%%%@&X'( (З(()H*,Й.0Px2X4К4țx6XK MMȞXN`NhN0pNHxN`NxNNNN؟NNN N8NPNhNNNNȠNHPOxQhR@SSS@TT8T`V(W@XXHX`Xx@YHYPYؤYY Y8PZhXZ`ZZȥZZP[(X[@`[X[[[\8H]h]^ȧh^^((_X_`ha(bbHcxhd(eةef8hgh(hhȪihj((kXklhm(nn@np@oop`pp8qh@rsȭst(@uXvvw@xyHyxz@{د||8x}`0~~ذX(ȁPx8ȱ`@Іh@h0 X؋Hг0hش (H ص 8p@Xؖ(ض`x@ȗXPhط@X@Xظ0@HXКع 8p@X؛p HpОػ Xp0XpHؼ`0X0ȡн@X(Ph0оH(УPh h@0hXإH Hp(`Ч8@`x`0 ЯPhH(HXpP0Xp``0Xp`P8`@@(PxPX@h`@0XX`H8 8pHXPP`@ H0 `P`(H (%PH&3H507h8p9P;x?p?8@@@0@A`AxFXKPQ0Q``RRhSS 8TPTUHV0Wh(Z`e8fPPoXy0|`h(Xx(8`pP( x@8p@H( X0hX0Xxл P@(пP8x P(`8hX`P@(HP8@(h0HXH8x HX HXH`8(` hHp0(88 X  `hPH@ 0hH@P8x0H """"#@#Xx$%8&'('((0, ,P(..0/0P102203@H5688:h:: ;P;;@;h`<x>0B `CX J`KLP`MNO(P`Q@SxYPYxXZ\]_``bb cpdpe8fg 0hH h h (i pi 0jP k m n 0o0 Hsx s u pw x | Hx X @h`p (`@0`P X8hТ@HȮP0 @Hȴ`(X ؿpx0Xp @P`@x0x8`pH0``(@X80(8pP` X  !`"p%((&`&(+` .p!04!`7"p9h">" A#0C`#D#GP$J$Q$S8%PW%[%](&_&a 'bP'bh'0h'h'k((pX( u(v(w)xX)y)})h~*XP*H**x8+ +,x ,8,, (-x-x-H.../P/@//P80(00h11(2pp2222` 3(P333P3h444(5`5 5586 66"6#07@)x7+7,7.8/@8P586809099p9h=9=:>H:0D:Q@;@_;`e8<Pq<8== H>>>hp??`@@`pAA '`B)xB2B3Cp58C:CPGCK8DODRDU(E[EH^FP`HF@eFiFmHG@pGpHH0IIIJ0J`JPJ( KpKKpLx0LLLM0 PMM(:8N@FE  @WdOE  P>@FE  p>@FE 4$ HWAP B CBw A 4\ X>lA` A C Cm A d , ?A*)D C('&z A $ WHA B AL $ WHA B AL $ XHA B AL $< (XHA B AL $d PXHA B AL ,xXX#A A CO <Xc#AP B CCd T<HZ'#AP B CCa B E ,[d"A A AN A $ \A A A_ ,\\"A A AR  \ \,L\\+"A A AR < \T \,\T!A A AP  ] \, \Ts!A A AP  ]]Ll ]L!Ap A AD F Bq B $|`@A D AI L (`, A"!C A BGBY A D4 bp AD A JC O B D| 0d_ A$#C A C"!GE B i0AB <;A0A BO A N B <P<A0A BO A N B 4$<A0A ABY A \h4 h4WA@A ACq A 4 i=A0A ACc A 4$ jA0A ACc A 4\ kA0A ACd A 4 HlA0A ACd A , mA<;C A:9C6G87,AC $ (A:9D A874@nA@A ADg A 4<ntA E A AR  AA 4t oxAEA AS AA x; 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