Class: Digiproc::Probability::TheoreticalGaussianDistribution

Inherits:
Object
  • Object
show all
Defined in:
lib/probability/theoretical_gaussian_distribution.rb

Overview

Class to calculate probabilities based off of a gaussian distributed random variable.

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(mean:, stddev:, generator_strategy: Digiproc::Strategies::GaussianGeneratorBoxMullerStrategy) ⇒ TheoreticalGaussianDistribution

Returns a new instance of TheoreticalGaussianDistribution.



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# File 'lib/probability/theoretical_gaussian_distribution.rb', line 7

def initialize(mean: , stddev: , generator_strategy: Digiproc::Strategies::GaussianGeneratorBoxMullerStrategy)
    @mean, @stddev = mean, stddev
    @variance = stddev ** 2
    @generator_strategy = generator_strategy.new(mean, stddev)
end

Instance Attribute Details

#mean ⇒ Object (readonly)

Returns the value of attribute mean.



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# File 'lib/probability/theoretical_gaussian_distribution.rb', line 5

def mean
  @mean
end

#stddev ⇒ Object (readonly)

Returns the value of attribute stddev.



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# File 'lib/probability/theoretical_gaussian_distribution.rb', line 5

def stddev
  @stddev
end

#variance ⇒ Object (readonly)

Returns the value of attribute variance.



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# File 'lib/probability/theoretical_gaussian_distribution.rb', line 5

def variance
  @variance
end

Instance Method Details

#cdf(x) ⇒ Object

Return the cdf [Float] of an input x [Float] gd = Digiproc::Probability::TheoreticalGaussianDistribution.new(mean: 0, stddev: 1) gd.cdf(0.3) # => 0.6179114221889526



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# File 'lib/probability/theoretical_gaussian_distribution.rb', line 17

def cdf(x)
    1 - q(x)
end

#p_between(lower, upper) ⇒ Object

Return the probability [Float] of the random variable being between an upper [Float] and lower [Float] value gd = Digiproc::Probability::TheoreticalGaussianDistribution.new(mean: 0, stddev: 1) gd.p_between(-1, 1) # => 0.6826894921370859



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# File 'lib/probability/theoretical_gaussian_distribution.rb', line 34

def p_between(lower, upper)
    cdf(upper) - cdf(lower)
end

#p_outside(lower, upper) ⇒ Object

Return the probability [Float] of the random variable being outside an upper [Float] and lower [Float] value gd = Digiproc::Probability::TheoreticalGaussianDistribution.new(mean: 0, stddev: 1) gd.p_outside(-1, 1) # => 0.31731050786291415



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# File 'lib/probability/theoretical_gaussian_distribution.rb', line 42

def p_outside(lower, upper)
    cdf(lower) + q(upper)
end

#q(x) ⇒ Object

Return the q value [Float] of an input x [Float] gd = Digiproc::Probability::TheoreticalGaussianDistribution.new(mean: 0, stddev: 1) gd.q(0.3) # => 0.3820885778110474



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# File 'lib/probability/theoretical_gaussian_distribution.rb', line 25

def q(x)
    xform_x = xform_x_to_standard(x)
    0.5 * Math.erfc(xform_x  / (2 ** 0.5))
end

#rand ⇒ Object

Outputs a single random number from the gaussian distribution gd.rand # => 1.4173209026395848



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# File 'lib/probability/theoretical_gaussian_distribution.rb', line 49

def rand
    @generator_strategy.rand
end