# Posts tagged pymc3.Beta

## Hierarchical Binomial Model: Rat Tumor Example

This short tutorial demonstrates how to use PyMC3 to do inference for the rat tumour example found in chapter 5 of Bayesian Data Analysis 3rd Edition . Readers should already be familliar with the PyMC3 API.

## Hierarchical Partial Pooling

Suppose you are tasked with estimating baseball batting skills for several players. One such performance metric is batting average. Since players play a different number of games and bat in different positions in the order, each player has a different number of at-bats. However, you want to estimate the skill of all players, including those with a relatively small number of batting opportunities.

The Dirichlet process is a flexible probability distribution over the space of distributions. Most generally, a probability distribution, $$P$$, on a set $$\Omega$$ is a [measure](https://en.wikipedia.org/wiki/Measure_(mathematics%29) that assigns measure one to the entire space ($$P(\Omega) = 1$$). A Dirichlet process $$P \sim \textrm{DP}(\alpha, P_0)$$ is a measure that has the property that, for every finite disjoint partition $$S_1, \ldots, S_n$$ of $$\Omega$$,