Class: ERV::GaussianDistribution

Inherits:
Distribution show all
Defined in:
lib/erv/gaussian_distribution.rb

Constant Summary

Constants inherited from Distribution

Distribution::DEFAULT_SEED

Instance Method Summary collapse

Constructor Details

#initialize(opts = {}) ⇒ GaussianDistribution

Returns a new instance of GaussianDistribution.

Raises:

  • (ArgumentError) 


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# File 'lib/erv/gaussian_distribution.rb', line 7

def initialize(opts={})
  super(opts)

  raise ArgumentError unless opts[:mean] and opts[:sd]
  @mu    = opts[:mean].to_f
  @sigma = opts[:sd].to_f
end

Instance Method Details

#mean ⇒ Object 



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# File 'lib/erv/gaussian_distribution.rb', line 27

def mean
  @mu
end

#sample ⇒ Object 



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# File 'lib/erv/gaussian_distribution.rb', line 15

def sample
  # Use Box-Muller algorithm (see [KROESE11], section 4.2.11, algorithm
  # 4.47) to obtain x ~ N(0,1).
  u_1 = @rng.rand
  u_2 = @rng.rand
  x = Math.sqrt(-2.0 * Math.log(u_1)) * Math.cos(2.0 * Math::PI * u_2)

  # Use location-scale transformation to obtain a N(\mu, \sigma^2)
  # distribution. See [KROESE11], section 3.1.2.2.
  @mu + @sigma * x
end

#variance ⇒ Object 



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# File 'lib/erv/gaussian_distribution.rb', line 31

def variance
  @sigma ** 2
end