numpy/scipy distributions

分布

http://docs.scipy.org/doc/numpy/reference/routines.random.html#distributions

|name|arguments| |—-|———| |beta|(a, b[, size])| |binomial|(n, p[, size])| |chisquare|(df[, size])| |dirichlet|(alpha[, size])| |exponential|([scale, size])| |f|(dfnum, dfden[, size])| |gamma|(shape[, scale, size])| |geometric|(p[, size])| |gumbel|([loc, scale, size])| |hypergeometric|(ngood, nbad, nsample[, size])| |laplace|([loc, scale, size])| |logistic|([loc, scale, size])| |lognormal|([mean, sigma, size])| |logseries|(p[, size])| |multinomial|(n, pvals[, size])| |multivariate_normal|(mean, cov[, size])| |negative_binomial|(n, p[, size])| |noncentral_chisquare|(df, nonc[, size])| |noncentral_f|(dfnum, dfden, nonc[, size])| |normal|([loc, scale, size])| |pareto|(a[, size])| |poisson|([lam, size])| |power|(a[, size])| |rayleigh|([scale, size])| |standard_cauchy|([size])| |standard_exponential|([size])| |standard_gamma|(shape[, size])| |standard_normal|([size])| |standard_t|(df[, size])| |triangular|(left, mode, right[, size])| |uniform|([low, high, size])| |vonmises|(mu, kappa[, size])| |wald|(mean, scale[, size])| |weibull|(a[, size])| |zipf |(a[, size])|

scipyの分布

continuous

http://docs.scipy.org/doc/scipy/reference/stats.html#continuous-distributions

multivariate

http://docs.scipy.org/doc/scipy/reference/stats.html#multivariate-distributions

discrete

http://docs.scipy.org/doc/scipy/reference/stats.html#discrete-distributions