API Reference#
This reference provides detailed documentation for all modules, classes, and methods in the current release of PyMC experimental.
|
Subclass of PyMC Model that implements functionality for automatic marginalization of variables in the logp transformation |
|
ModelBuilder can be used to provide an easy-to-use API (similar to scikit-learn) for models and help with deployment. |
Inference#
|
Fit a model with an inference algorithm |
Distributions#
|
Univariate Generalized Extreme Value log-likelihood |
|
Generalized Poisson. |
|
A Discrete Markov Chain is a sequence of random variables |
|
R2D2M2CP Prior. |
|
Approximate a distribution with a histogram potential. |
Utils#
|
Clone a PyMC model. |
|
Interpolate sparse grid to dense grid using bsplines. |
|
Create a prior from posterior using MvNormal approximation. |
Convert Model to FunctionGraph. |
|
|
Convert FunctionGraph to PyMC model. |