67 lines
1.5 KiB
Ruby
67 lines
1.5 KiB
Ruby
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module Statistics
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module Distribution
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class Weibull
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attr_accessor :shape, :scale # k and lambda
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def initialize(k, lamb)
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self.shape = k.to_f
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self.scale = lamb.to_f
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end
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def cumulative_function(random_value)
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return 0 if random_value < 0
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1 - Math.exp(-((random_value/scale) ** shape))
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end
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def density_function(value)
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return if shape <= 0 || scale <= 0
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return 0 if value < 0
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left = shape/scale
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center = (value/scale)**(shape - 1)
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right = Math.exp(-((value/scale)**shape))
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left * center * right
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end
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def mean
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scale * Math.gamma(1 + (1/shape))
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end
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def mode
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return 0 if shape <= 1
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scale * (((shape - 1)/shape) ** (1/shape))
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end
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def variance
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left = Math.gamma(1 + (2/shape))
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right = Math.gamma(1 + (1/shape)) ** 2
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(scale ** 2) * (left - right)
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end
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# Using the inverse CDF function, also called quantile, we can calculate
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# a random sample that follows a weibull distribution.
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#
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# Formula extracted from https://www.taygeta.com/random/weibull.html
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def random(elements: 1, seed: Random.new_seed)
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results = []
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srand(seed)
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elements.times do
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results << ((-1/scale) * Math.log(1 - rand)) ** (1/shape)
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end
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if elements == 1
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results.first
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else
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results
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end
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end
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end
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end
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end
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