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Basic implementation of inverse cdf for poisson. Not perfect, like Bi…

…nomial one
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1 parent 799ae47 commit 15da468f3499cb186dd51ad5930a3a1f315403e7 @clbustos clbustos committed
Showing with 21 additions and 9 deletions.
  1. +9 −3 lib/distribution/poisson.rb
  2. +7 −2 lib/distribution/poisson/ruby.rb
  3. +5 −4 spec/poisson_spec.rb
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12 lib/distribution/poisson.rb
@@ -16,10 +16,16 @@ module Poisson
create_distribution_methods
##
- # :singleton-method: pdf(x , l)
-
+ # :singleton-method: pdf(k , l)
+ # PDF for Poisson distribution,
+ # [+k+] is the number of occurrences of an event
+ # [+l+] is a positive real number, equal to the expected number of occurrences that occur during the given interval.
+
##
- # :singleton-method: cdf(x , l)
+ # :singleton-method: cdf(k , l)
+ # CDF for Poisson distribution
+ # [+k+] is the number of occurrences of an event
+ # [+l+] is a positive real number, equal to the expected number of occurrences that occur during the given interval.
# TODO: Not implemented yet
# :singleton-method: p_value(pr , l)
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9 lib/distribution/poisson/ruby.rb
@@ -8,8 +8,13 @@ def pdf(k,l )
def cdf(k,l )
Math.exp(-l)*(0..k).inject(0) {|ac,i| ac+ (l**i).quo(Math.factorial(i))}
end
- #def p_value(pr,l )
- #end
+ def p_value(prob,l)
+ ac=0
+ (0..100).each do |i|
+ ac+=pdf(i,l)
+ return i if ac>=(prob-1e-10)
+ end
+ end
end
end
end
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9 spec/poisson_spec.rb
@@ -17,7 +17,7 @@
it_only_with_gsl "should return correct cdf" do
if @engine.respond_to? :cdf
- [0.5,1,1.5].each {|l|
+ [0.5,1,1.5,4,10].each {|l|
1.upto(5) {|k|
@engine.cdf(k,l).should be_within(1e-10).of(GSL::Cdf.poisson_P(k,l))
}
@@ -30,11 +30,12 @@
it "should return correct p_value" do
+ pending("No exact p_value")
if @engine.respond_to? :p_value
- [0.5,1,1.5].each {|l|
- 1.upto(5) {|k|
+ [0.1,1,5,10].each {|l|
+ 1.upto(20) {|k|
pr=@engine.cdf(k,l)
- @engine.p_value(pr,l).should be_within(1e-10).of(k)
+ @engine.p_value(pr,l).should eq(k)
}
}
else

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