Module: Statsample::CovariateMatrix
- Includes:
- NamedMatrix
- Defined in:
- lib/statsample/matrix.rb
Overview
Module to add method for variance/covariance and correlation matrices
Usage
matrix=Matrix[[1,2],[2,3]]
matrix.extend CovariateMatrix
Constant Summary collapse
- @@covariatematrix =
0
Instance Method Summary collapse
-
#_type ⇒ Object
Get type of covariate matrix.
- #_type=(t) ⇒ Object
- #correlation ⇒ Object
- #get_new_name ⇒ Object
- #report_building(generator) ⇒ Object
-
#submatrix(rows, columns = nil) ⇒ Object
Select a submatrix of factors.
-
#variance(k) ⇒ Object
Get variance for field k.
Methods included from NamedMatrix
#fields, #fields=, #fields_x, #fields_x=, #fields_y, #fields_y=, #name, #name=
Methods included from Summarizable
Instance Method Details
#_type ⇒ Object
Get type of covariate matrix. Could be :covariance or :correlation
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# File 'lib/statsample/matrix.rb', line 226 def _type if row_size==column_size if row_size.times.find {|i| self[i,i]!=1.0} :covariance else :correlation end else @type end end |
#_type=(t) ⇒ Object
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# File 'lib/statsample/matrix.rb', line 238 def _type=(t) @type=t end |
#correlation ⇒ Object
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# File 'lib/statsample/matrix.rb', line 241 def correlation if(_type==:covariance) matrix=Matrix.rows(row_size.times.collect { |i| column_size.times.collect { |j| if i==j 1.0 else self[i,j].quo(Math::sqrt(self[i,i])*Math::sqrt(self[j,j])) end } }) matrix.extend CovariateMatrix matrix.fields_x=fields_x matrix.fields_y=fields_y matrix._type=:correlation matrix else self end end |
#get_new_name ⇒ Object
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# File 'lib/statsample/matrix.rb', line 269 def get_new_name @@covariatematrix+=1 _("Covariate matrix %d") % @@covariatematrix end |
#report_building(generator) ⇒ Object
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# File 'lib/statsample/matrix.rb', line 318 def report_building(generator) @name||= (_type==:correlation ? _("Correlation"):_("Covariance"))+_(" Matrix") generator.table(:name=>@name, :header=>[""]+fields_y) do |t| row_size.times {|i| t.row([fields_x[i]]+row(i).to_a.collect {|i1| i1.nil? ? "--" : sprintf("%0.3f",i1).gsub("0.",".") }) } end end |
#submatrix(rows, columns = nil) ⇒ Object
Select a submatrix of factors. If you have a correlation matrix with a, b and c, you could obtain a submatrix of correlations of a and b, b and c or a and b
You could use labels or index to select the factors. If you don’t specify columns, its will be equal to rows.
Example:
a=Matrix[[1.0, 0.3, 0.2],
[0.3, 1.0, 0.5],
[0.2, 0.5, 1.0]]
a.extend CovariateMatrix
a.fields=%w{a b c}
a.submatrix(%w{c a}, %w{b})
=> Matrix[[0.5],[0.3]]
a.submatrix(%w{c a})
=> Matrix[[1.0, 0.2] , [0.2, 1.0]]
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# File 'lib/statsample/matrix.rb', line 291 def submatrix(rows,columns = nil) raise ArgumentError, "rows shouldn't be empty" if rows.respond_to? :size and rows.size == 0 columns ||= rows # Convert all fields on index row_index = rows.collect do |v| r = v.is_a?(Numeric) ? v : fields_x.index(v) raise "Index #{v} doesn't exists on matrix" if r.nil? r end column_index = columns.collect do |v| r = v.is_a?(Numeric) ? v : fields_y.index(v) raise "Index #{v} doesn't exists on matrix" if r.nil? r end fx=row_index.collect {|v| fields_x[v]} fy=column_index.collect {|v| fields_y[v]} matrix = Matrix.rows(row_index.collect { |i| column_index.collect { |j| self[i, j] }}) matrix.extend CovariateMatrix matrix.fields_x = fx matrix.fields_y = fy matrix._type = _type matrix end |
#variance(k) ⇒ Object
Get variance for field k
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# File 'lib/statsample/matrix.rb', line 265 def variance(k) submatrix([k])[0,0] end |