test_statistics.rb in statsample-0.4.0

- old
+ new

@@ -62,11 +62,10 @@
 	end
 	end
 #assert_equal(expected,obt)
     end
     def test_prop_pearson
-	if HAS_GSL    
         assert_in_delta(0.42, Statsample::Bivariate.prop_pearson(Statsample::Bivariate.t_r(0.084,94), 94),0.01)
         assert_in_delta(0.65, Statsample::Bivariate.prop_pearson(Statsample::Bivariate.t_r(0.046,95), 95),0.01)
         r=0.9
         n=100
         t=Statsample::Bivariate.t_r(r,n)
@@ -78,15 +77,10 @@
         n=100
         t=Statsample::Bivariate.t_r(r,n)
         assert(Statsample::Bivariate.prop_pearson(t,n,:both)<0.05)
         assert(Statsample::Bivariate.prop_pearson(t,n,:right)>0.05)
         assert(Statsample::Bivariate.prop_pearson(t,n,:left)<0.05)
-
-        
-	else
-		puts "Bivariate.prop_pearson not tested (no ruby-gsl)"
-	end
     end
 	def test_covariance
 		if HAS_GSL
 			v1=[6,5,4,7,8,4,3,2].to_vector(:scale)
 			v2=[2,3,7,8,6,4,3,2].to_vector(:scale)
@@ -128,15 +122,11 @@
 	end
     def test_estimation_mean              
         v=([42]*23+[41]*4+[36]*1+[32]*1+[29]*1+[27]*2+[23]*1+[19]*1+[16]*2+[15]*2+[14,11,10,9,7]+ [6]*3+[5]*2+[4,3]).to_vector(:scale)
         assert_equal(50,v.size)
         assert_equal(1471,v.sum())
-	if HAS_GSL
         limits=Statsample::SRS.mean_confidence_interval_z(v.mean(), v.sds(), v.size,676,0.80)
-       else
-	       puts "SRS.mean_confidence_interval_z not tested (no ruby-gsl)"
-	       end
     end
     def test_estimation_proportion
         # total
         pop=3042
         sam=200
@@ -146,17 +136,12 @@
         # confidence limits
         pop=500
         sam=100
         prop=0.37
         a=0.95
-	if HAS_GSL
         l= Statsample::SRS.proportion_confidence_interval_z(prop, sam, pop, a)
         assert_in_delta(0.28,l[0],0.01)
         assert_in_delta(0.46,l[1],0.01)
-	else
-	       puts "SRS.proportion_confidence_interval_z not tested (no ruby-gsl)"
-		
-		end
     end
     def test_ml
         if(true)
 		real=[1,1,1,1].to_vector(:scale)
 		