lib/statsample/factor/principalaxis.rb in statsample-0.14.0 vs lib/statsample/factor/principalaxis.rb in statsample-0.14.1

@@ -122,21 +122,22 @@
       pca=PCA.new(::Matrix.rows(work_matrix))
       @initial_eigenvalues=pca.eigenvalues
       prev_sum=prev_com.inject(0) {|ac,v| ac+v}
       @iterations=0
       t.times do |i|
+        "#{@name}: Iteration #{i}" if $DEBUG
         @iterations+=1
         prev_com.each_with_index{|v,it|
           work_matrix[it][it]=v
         }
         pca=PCA.new(::Matrix.rows(work_matrix))
         @communalities=pca.communalities(m)
         @eigenvalues=pca.eigenvalues
         com_sum = @communalities.inject(0) {|ac,v| ac+v}
         jump=true
         
-        break if (com_sum-prev_sum).abs<@delta
+        break if (com_sum-prev_sum).abs < @delta
         @communalities.each_with_index do |v2,i2|
           raise "Variable #{i2} with communality > 1" if v2>1.0
         end
         prev_sum=com_sum
         prev_com=@communalities
@@ -151,15 +152,20 @@
     end
     alias :compute :iterate 
     
     def initial_communalities
       if @initial_communalities.nil?
+        
         if @smc
+          # Based on O'Connors(2000)
+          @initial_communalities=@matrix.inverse.diagonal.map{|i| 1-(1.quo(i))}
+=begin
         @initial_communalities=@matrix.column_size.times.collect {|i|
           rxx , rxy = PrincipalAxis.separate_matrices(@matrix,i)
           matrix=(rxy.t*rxx.inverse*rxy)
           matrix[0,0]
         }
+=end
         else
           @initial_communalities=[1.0]*@matrix.column_size
         end
       end      
       @initial_communalities