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Update api docs for distributions (#5266)
* update api docs for distributions * add aeppl to intersphinx mapping Co-authored-by: Michael Osthege <michael.osthege@outlook.com>
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‎.gitignore

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# Sphinx
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_build
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docs/jupyter_execute
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docs/**/generated/*
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# Merge tool
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*.orig

‎docs/source/Makefile renamed to ‎Makefile

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SPHINXOPTS =
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SPHINXBUILD = sphinx-build
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PAPER =
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BUILDDIR = _build
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SOURCEDIR = docs/source
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BUILDDIR = docs/_build
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# User-friendly check for sphinx-build
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ifeq ($(shell which $(SPHINXBUILD) >/dev/null 2>&1; echo $$?), 1)
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clean:
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rm -rf $(BUILDDIR)/*
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rm -rf $(SOURCEDIR)/api/**/generated
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rm -rf docs/jupyter_execute
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html:
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$(SPHINXBUILD) -b html $(ALLSPHINXOPTS) $(BUILDDIR)/html
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$(SPHINXBUILD) $(SOURCEDIR) $(BUILDDIR) -b html
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@echo
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@echo "Build finished. The HTML pages are in $(BUILDDIR)/html."
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‎docs/source/api.rst

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api/smc
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api/step_methods
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api/inference
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api/plots
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Indices and tables
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===================
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--------------
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API extensions
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--------------
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* :ref:`genindex`
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* :ref:`modindex`
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* :ref:`search`
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Plots, stats and diagnostics
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----------------------------
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Plots, stats and diagnostics are delegated to the
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:doc:`ArviZ <arviz:index>`.
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library, a general purpose library for
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"exploratory analysis of Bayesian models".
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* Functions from the `arviz.plots` module are available through ``pymc.<function>`` or ``pymc.plots.<function>``,
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but for their API documentation please refer to the :ref:`ArviZ documentation <arviz:plot_api>`.
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* Functions from the `arviz.stats` module are available through ``pymc.<function>`` or ``pymc.stats.<function>``,
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but for their API documentation please refer to the :ref:`ArviZ documentation <arviz:stats_api>`.
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ArviZ is a dependency of PyMC and so, in addition to the locations described above,
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importing ArviZ and using ``arviz.<function>`` will also work without any extra installation.
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Generalized Linear Models (GLMs)
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--------------------------------
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Generalized Linear Models are delegated to the
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`Bambi <https://bambinos.github.io/bambi>`_.
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library, a high-level Bayesian model-building
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interface built on top of PyMC.
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Bambi is not a dependency of PyMC and should be installed in addition to PyMC
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to use it to generate PyMC models via formula syntax.

‎docs/source/api/distributions/continuous.rst

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Continuous
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**********
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.. currentmodule:: pymc.distributions.continuous
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.. currentmodule:: pymc
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.. autosummary::
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:toctree: generated/
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Uniform
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Flat
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Moyal
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AsymmetricLaplace
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PolyaGamma
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.. automodule:: pymc.distributions.continuous
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:members:

‎docs/source/api/distributions/discrete.rst

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Discrete
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********
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.. currentmodule:: pymc.distributions.discrete
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.. currentmodule:: pymc
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.. autosummary::
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:toctree: generated
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Binomial
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BetaBinomial
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Categorical
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OrderedLogistic
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OrderedProbit
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.. automodule:: pymc.distributions.discrete
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:members:

‎docs/source/api/distributions/mixture.rst

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Mixture
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*******
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.. currentmodule:: pymc.distributions.mixture
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.. currentmodule:: pymc
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.. autosummary::
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:toctree: generated
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Mixture
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NormalMixture
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MixtureSameFamily
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.. automodule:: pymc.distributions.mixture
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:members:

‎docs/source/api/distributions/multivariate.rst

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Multivariate
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************
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.. currentmodule:: pymc.distributions.multivariate
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.. currentmodule:: pymc
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.. autosummary::
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:toctree: generated
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MvStudentT
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MatrixNormal
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KroneckerNormal
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CAR
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.. automodule:: pymc.distributions.multivariate
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:members:

‎docs/source/api/distributions/simulator.rst

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Simulator
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**********
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.. currentmodule:: pymc.distributions.simulator
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.. currentmodule:: pymc
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:toctree: generated
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Simulator
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:members:

‎docs/source/api/distributions/timeseries.rst

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Timeseries
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**********
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.. currentmodule:: pymc.distributions.timeseries
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.. currentmodule:: pymc
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:toctree: generated
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AR1
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AR
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GaussianRandomWalk
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:members:

‎docs/source/api/distributions/transforms.rst

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****************************************************************
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Transformations of a random variable from one space to another
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****************************************************************
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Note that for convenience these entities can be addressed as
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``pm.transforms.``\ *X* for any name *X*, although they are actually
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implemented as ``pm.distributions.transforms.``\ *X*.
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.. currentmodule:: pymc.distributions.transforms
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.. contents ::
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..
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.. autosummary::
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Transform
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stick_breaking
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logodds
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interval
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log_exp_m1
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ordered
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log
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sum_to_1
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circular
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CholeskyCovPacked
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Chain
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***************
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Transformations
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***************
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.. currentmodule:: pymc.transforms
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Transform Instances
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~~~~~~~~~~~~~~~~~~~
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Transform instances are the entities that should be used in the
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``transform`` parameter to a random variable constructor. These are
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initialized instances of the Transform Classes, which are described
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below.
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.. glossary::
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``stick_breaking``
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Instantiation of :class:`~pymc.distributions.transforms.StickBreaking`
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:class:`~pymc.distributions.transforms.Transform` class for use in the ``transform``
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argument of a random variable.
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``logodds``
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:class:`~pymc.distributions.transforms.LogOdds` :class:`~pymc.distributions.transforms.Transform` class
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for use in the ``transform`` argument of a random variable.
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``interval``
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:class:`~pymc.distributions.transforms.Interval` :class:`~pymc.distributions.transforms.Transform` class
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for use in the ``transform`` argument of a random variable.
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``log_exp_m1``
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:class:`~pymc.distributions.transforms.LogExpM1` :class:`~pymc.distributions.transforms.Transform` class
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``transform`` parameter to a random variable constructor.
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``lowerbound``
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:class:`~pymc.distributions.transforms.SumTo1` :class:`~pymc.distributions.transforms.Transform` class
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Transform Base Classes
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~~~~~~~~~~~~~~~~~~~~~~
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Typically the programmer will not use these directly.
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.. autoclass:: Transform
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:members:
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.. autosummary::
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:toctree: generated
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simplex
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logodds
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interval
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log_exp_m1
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ordered
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log
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sum_to_1
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circular
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.. autoclass:: Chain
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.. autosummary::
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:toctree: generated
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Chain
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CholeskyCovPacked
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.. autoclass:: Log
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:members:
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.. autoclass:: LogExpM1
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:members:
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.. autoclass:: LogOdds
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.. autoclass:: Interval
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.. autoclass:: Ordered
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.. autoclass:: SumTo1
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:members:
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.. autoclass:: StickBreaking
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.. autoclass:: Circular
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.. autosummary::
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:toctree: generated
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LogExpM1
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Ordered
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SumTo1

‎docs/source/api/distributions/utilities.rst

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*******************************************
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Distribution utility classes and functions
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**********************
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Distribution utilities
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**********************
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.. currentmodule:: pymc.distributions
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.. currentmodule:: pymc
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:toctree: generated/
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Distribution
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Discrete
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Continuous
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NoDistribution
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DensityDist
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.. autoclass:: Discrete
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.. autoclass:: Continuous
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.. autoclass:: NoDistribution
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Discrete
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Continuous
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NoDistribution
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DensityDist

‎docs/source/api/glm.rst

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‎docs/source/api/plots.rst

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‎docs/source/api/stats.rst

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