RandomState.pareto()

RandomState.pareto(a, size=None) Draw samples from a Pareto II or Lomax distribution with specified shape.

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numpy.random.gamma()

numpy.random.gamma(shape, scale=1.0, size=None) Draw samples from a Gamma distribution. Samples are drawn from a

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numpy.random.chisquare()

numpy.random.chisquare(df, size=None) Draw samples from a chi-square distribution. When df independent

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RandomState.uniform()

RandomState.uniform(low=0.0, high=1.0, size=None) Draw samples from a uniform distribution. Samples are

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RandomState.set_state()

RandomState.set_state(state) Set the internal state of the generator from a tuple. For use if one has

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RandomState.chisquare()

RandomState.chisquare(df, size=None) Draw samples from a chi-square distribution. When df

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numpy.random.negative_binomial()

numpy.random.negative_binomial(n, p, size=None) Draw samples from a negative binomial distribution. Samples

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RandomState.laplace()

RandomState.laplace(loc=0.0, scale=1.0, size=None) Draw samples from the Laplace or double exponential distribution

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RandomState.wald()

RandomState.wald(mean, scale, size=None) Draw samples from a Wald, or inverse Gaussian, distribution. As

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numpy.random.rayleigh()

numpy.random.rayleigh(scale=1.0, size=None) Draw samples from a Rayleigh distribution. The

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