numpy.random.noncentral_f()

numpy.random.noncentral_f(dfnum, dfden, nonc, size=None) Draw samples from the noncentral F distribution. Samples

2017-01-10 18:18:07
RandomState.beta()

RandomState.beta(a, b, size=None) Draw samples from a Beta distribution. The Beta distribution is a special

2017-01-10 18:19:31
numpy.random.binomial()

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

2017-01-10 18:17:58
RandomState.standard_normal()

RandomState.standard_normal(size=None) Draw samples from a standard Normal distribution (mean=0, stdev=1)

2017-01-10 18:19:48
RandomState.exponential()

RandomState.exponential(scale=1.0, size=None) Draw samples from an exponential distribution. Its

2017-01-10 18:19:34
RandomState.randint()

RandomState.randint(low, high=None, size=None, dtype='l') Return random integers from low (inclusive)

2017-01-10 18:19:44
numpy.random.power()

numpy.random.power(a, size=None) Draws samples in [0, 1] from a power distribution with positive exponent a - 1. Also

2017-01-10 18:18:10
numpy.random.dirichlet()

numpy.random.dirichlet(alpha, size=None) Draw samples from the Dirichlet distribution. Draw size

2017-01-10 18:18:00
RandomState.gumbel()

RandomState.gumbel(loc=0.0, scale=1.0, size=None) Draw samples from a Gumbel distribution. Draw samples

2017-01-10 18:19:36
RandomState.binomial()

RandomState.binomial(n, p, size=None) Draw samples from a binomial distribution. Samples are drawn from

2017-01-10 18:19:32