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module Statsample
module Bivariate
# = Pearson correlation coefficient (r)
#
# The moment-product Pearson's correlation coefficient, known as 'r'
# is a measure of bivariate associate between two continous
# variables.
#
# == Usage
# a = [1,2,3,4,5,6].to_scale
# b = [2,3,4,5,6,7].to_scale
# pearson = Statsample::Bivariate::Pearson.new(a,b)
# puts pearson.r
# puts pearson.t
# puts pearson.probability
# puts pearson.summary
#
class Pearson
include Statsample::Test
include Summarizable
# Name of correlation
attr_accessor :name
# Tails for probability (:both, :left or :right)
attr_accessor :tails
attr_accessor :n
def initialize(v1,v2,opts=Hash.new)
@v1_name,@v2_name = v1.name,v2.name
@v1,@v2 = Statsample.only_valid_clone(v1,v2)
@n=@v1.size
opts_default={
:name=>_("Correlation (%s - %s)") % [@v1_name, @v2_name],
:tails=>:both
}
@opts=opts.merge(opts_default)
@opts.each{|k,v|
self.send("#{k}=",v) if self.respond_to? k
}
end
def r
Statsample::Bivariate.pearson(@v1,@v2)
end
def t
Statsample::Bivariate.t_pearson(@v1,@v2)
end
def probability
p_using_cdf(Distribution::T.cdf(t, @v1.size-2), tails)
end
def report_building(builder)
builder.text(_("%s : r=%0.3f (t:%0.3f, g.l.=%d, p:%0.3f / %s tails)") % [@name, r,t, (n-2), probability, tails])
end
end
end
end
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17 entries across 17 versions & 1 rubygems