module Statsample::Regression

Module for regression procedures. ↑

Use the method on this class to generate analysis. If you need more control, you can create and control directly the objects who computes the regressions.

Module for regression procedures. ↑

Use the method on this class to generate analysis. If you need more control, you can create and control directly the objects who computes the regressions.

Constants

LinearDependency

Public Class Methods

multiple(ds,y_var, opts=Hash.new) click to toggle source

Creates one of the Statsample::Regression::Multiple object, for OLS multiple regression. Parameters:

  • ds: Dataset.

  • y: Name of dependent variable.

  • opts: A hash with options

    • missing_data: Could be

      • :listwise: delete cases with one or more empty data (default).

      • :pairwise: uses correlation matrix. Use with caution.

Usage:

lr=Statsample::Regression::multiple(ds,'y')
# File lib/statsample/regression.rb, line 53
def self.multiple(ds,y_var, opts=Hash.new)
  missing_data= (opts[:missing_data].nil? ) ? :listwise : opts.delete(:missing_data)
  if missing_data==:pairwise
     Statsample::Regression::Multiple::RubyEngine.new(ds,y_var, opts)
  else
    if Statsample.has_gsl? and false
      Statsample::Regression::Multiple::GslEngine.new(ds, y_var, opts)
    else
      ds2=ds.dup_only_valid
      Statsample::Regression::Multiple::RubyEngine.new(ds2,y_var, opts)
    end
  end
end
simple(x,y) click to toggle source

Create a Statsample::Regression::Simple object, for simple regression

Usage:

x=100.times.collect {|i| rand(100)}.to_scale
y=100.times.collect {|i| 2+x[i]*2+rand()}.to_scale
sr=Statsample::Regression.simple(x,y)
sr.a
=> 2.51763295177808
sr.b
=> 1.99973746599856
sr.r
=> 0.999987881153254

# File lib/statsample/regression.rb, line 37
def self.simple(x,y)
  Statsample::Regression::Simple.new_from_vectors(x,y)
end