numpy.random.noncentral_f(dfnum, dfden, nonc, size=None) Draw samples from the noncentral F distribution. Samples
RandomState.beta(a, b, size=None) Draw samples from a Beta distribution. The Beta distribution is a special
numpy.random.binomial(n, p, size=None) Draw samples from a binomial distribution. Samples are drawn from a binomial
RandomState.standard_normal(size=None) Draw samples from a standard Normal distribution (mean=0, stdev=1)
RandomState.exponential(scale=1.0, size=None) Draw samples from an exponential distribution. Its
RandomState.randint(low, high=None, size=None, dtype='l') Return random integers from low (inclusive)
numpy.random.power(a, size=None) Draws samples in [0, 1] from a power distribution with positive exponent a - 1. Also
numpy.random.dirichlet(alpha, size=None) Draw samples from the Dirichlet distribution. Draw size
RandomState.gumbel(loc=0.0, scale=1.0, size=None) Draw samples from a Gumbel distribution. Draw samples
RandomState.binomial(n, p, size=None) Draw samples from a binomial distribution. Samples are drawn from
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