.. currentmodule:: statsmodels.sandbox.distributions .. _distributions: Distributions ============= This section collects various additional functions and methods for statistical distributions. Empirical Distributions ----------------------- .. currentmodule:: statsmodels.distributions.empirical_distribution .. autosummary:: :toctree: generated/ ECDF StepFunction Distribution Extras ------------------- .. currentmodule:: statsmodels.sandbox.distributions.extras *Skew Distributions* .. autosummary:: :toctree: generated/ SkewNorm_gen SkewNorm2_gen ACSkewT_gen skewnorm2 *Distributions based on Gram-Charlier expansion* .. autosummary:: :toctree: generated/ pdf_moments_st pdf_mvsk pdf_moments NormExpan_gen *cdf of multivariate normal* wrapper for scipy.stats .. autosummary:: :toctree: generated/ mvstdnormcdf mvnormcdf 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. .. currentmodule:: statsmodels.sandbox.distributions.transformed .. autosummary:: :toctree: generated/ TransfTwo_gen Transf_gen ExpTransf_gen LogTransf_gen SquareFunc absnormalg invdnormalg loggammaexpg lognormalg negsquarenormalg squarenormalg squaretg