RandomState.zipf(a, size=None) Draw samples from a Zipf distribution. Samples are drawn from a Zipf distribution

RandomState.standard_exponential(size=None) Draw samples from the standard exponential distribution

RandomState.f(dfnum, dfden, size=None) Draw samples from an F distribution. Samples are drawn from an F distribution

RandomState.randn(d0, d1, ..., dn) Return a sample (or samples) from the ?standard normal? distribution. If

RandomState.lognormal(mean=0.0, sigma=1.0, size=None) Draw samples from a log-normal distribution. Draw

RandomState.multivariate_normal(mean, cov[, size]) Draw random samples from a multivariate normal

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

numpy.random.zipf(a, size=None) Draw samples from a Zipf distribution. Samples are drawn from a Zipf distribution

RandomState.multinomial(n, pvals, size=None) Draw samples from a multinomial distribution. The multinomial

numpy.random.noncentral_chisquare(df, nonc, size=None) Draw samples from a noncentral chi-square distribution