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) |
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