Class: Croupier::Distributions::Nbinomial

Inherits:
Croupier::Distribution show all
Defined in:
lib/croupier/distributions/nbinomial.rb

Overview

Negative Binomial Distribution Discrete probability distribution of the number of successes in a sequence of Bernoulli trials before a specified (non-random) number of failures (denoted size) occur.

Wikipedia – en.wikipedia.org/wiki/Negative_binomial_distribution

Instance Attribute Summary

Attributes inherited from Croupier::Distribution

#description, #name, #parameters

Class Method Summary collapse

Instance Method Summary collapse

Methods inherited from Croupier::Distribution

#configure, #generate_number, #params

Constructor Details

#initialize(options = {}) ⇒ Nbinomial

Returns a new instance of Nbinomial.

Raises:



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# File 'lib/croupier/distributions/nbinomial.rb', line 13

def initialize(options={})
  @name = "Negative binomial distribution"
  @description = "Discrete probability distribution of the number of successes in a sequence of Bernoulli trials before a specified (non-random) number of failures (denoted size) occur."
  configure(options)
  raise Croupier::InputParamsError, "Probability of success must be in the interval [0,1]" if params[:success] > 1 || params[:success] < 0
end

Class Method Details

.cli_name ⇒ Object 



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# File 'lib/croupier/distributions/nbinomial.rb', line 34

def self.cli_name
  "nbinomial"
end

.cli_options ⇒ Object 



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# File 'lib/croupier/distributions/nbinomial.rb', line 38

def self.cli_options
  {:options => [
     [:size, 'number of errors', {:type => :integer, :default => 1}],
     [:success, 'success probability of each trial', {:type=>:float, :short => "-p", :default => 0.5}]
   ],
   :banner => "Negative binomial distribution. Discrete probability distribution of the number of successes in a sequence of Bernoulli trials before a specified (non-random) number of failures (denoted size) occur."
  }
end

Instance Method Details

#default_parameters ⇒ Object 



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# File 'lib/croupier/distributions/nbinomial.rb', line 30

def default_parameters
  {:success => 0.5, :size => 1}
end

#generate_sample(n = 1) ⇒ Object

Fair point: it is not the inverse of the cdf, but it generates the distribution from an uniform.



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# File 'lib/croupier/distributions/nbinomial.rb', line 22

def generate_sample n=1
  generate_geometrics(n).each_slice(params[:size]).map do |sample|
    sample.inject(-params[:size], &:+) # Inject starts on -size because
    # this way it is equivalent to:
    # sample.map{|x| x - 1}.inject(&:+)
  end
end