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.. currentmodule:: statsmodels.sandbox.distributions
.. _distributions:
Distributions
=============
Introduction
------------
This section collects various additional functions and methods for statistical
distributions.
Sandbox Warning: The functions and objects in this category are still in the sandbox.
Many functions or classes have been tested on individual examples, but don't have a
(consistent or complete) test suite yet.
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
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