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Distributions

This section collects various additional functions and methods for statistical distributions.

Empirical Distributions

ECDF(x[, side]) Return the Empirical CDF of an array as a step function.
StepFunction(x, y[, ival, sorted, side]) A basic step function.

Distribution Extras

Skew Distributions

SkewNorm_gen() univariate Skew-Normal distribution of Azzalini
SkewNorm2_gen([momtype, a, b, xtol, ...]) univariate Skew-Normal distribution of Azzalini
ACSkewT_gen() univariate Skew-T distribution of Azzalini
skewnorm2 univariate Skew-Normal distribution of Azzalini

Distributions based on Gram-Charlier expansion

pdf_moments_st(cnt) Return the Gaussian expanded pdf function given the list of central moments (first one is mean).
pdf_mvsk(mvsk) Return the Gaussian expanded pdf function given the list of 1st, 2nd moment and skew and Fisher (excess) kurtosis.
pdf_moments(cnt) Return the Gaussian expanded pdf function given the list of central moments (first one is mean).
NormExpan_gen(args, **kwds) Gram-Charlier Expansion of Normal distribution

cdf of multivariate normal wrapper for scipy.stats

mvstdnormcdf(lower, upper, corrcoef, **kwds) standardized multivariate normal cumulative distribution function
mvnormcdf(upper, mu, cov[, lower]) multivariate normal cumulative distribution function

Univariate Distributions by non-linear Transformations

Univariate distributions can be generated from a non-linear transformation of an existing univariate distribution. Transf_gen is a class that can generate a new distribution from a monotonic transformation, TransfTwo_gen can use hump-shaped or u-shaped transformation, such as abs or square. The remaining objects are special cases.

TransfTwo_gen(kls, func, funcinvplus, ...) Distribution based on a non-monotonic (u- or hump-shaped transformation)
Transf_gen(kls, func, funcinv, *args, **kwargs) a class for non-linear monotonic transformation of a continuous random variable
ExpTransf_gen(kls, *args, **kwargs) Distribution based on log/exp transformation
LogTransf_gen(kls, *args, **kwargs) Distribution based on log/exp transformation
SquareFunc class to hold quadratic function with inverse function and derivative
absnormalg Distribution based on a non-monotonic (u- or hump-shaped transformation)
invdnormalg a class for non-linear monotonic transformation of a continuous random variable
loggammaexpg univariate distribution of a non-linear monotonic transformation of a
lognormalg a class for non-linear monotonic transformation of a continuous random variable
negsquarenormalg Distribution based on a non-monotonic (u- or hump-shaped transformation)
squarenormalg Distribution based on a non-monotonic (u- or hump-shaped transformation)
squaretg Distribution based on a non-monotonic (u- or hump-shaped transformation)