---
title: priors
sidebarTitle: priors
---

# `catalax.mcmc.priors`

## Classes

### `Prior` <sup><a href="https://github.com/JR-1991/Catalax/blob/master/catalax/mcmc/priors.py#L6" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>


Base class for all prior distributions used in Bayesian inference.

This class defines the interface for all prior distributions and provides
common functionality for serialization and representation.


**Methods:**

#### `type` <sup><a href="https://github.com/JR-1991/Catalax/blob/master/catalax/mcmc/priors.py#L17" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>

```python
type(self) -> str
```

Return the name of the prior distribution class.


### `Normal` <sup><a href="https://github.com/JR-1991/Catalax/blob/master/catalax/mcmc/priors.py#L22" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>


Normal (Gaussian) prior distribution.

Represents a normal distribution with mean μ and standard deviation σ.


### `TruncatedNormal` <sup><a href="https://github.com/JR-1991/Catalax/blob/master/catalax/mcmc/priors.py#L46" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>


Truncated Normal prior distribution.

Represents a normal distribution truncated to a specific range.


### `Uniform` <sup><a href="https://github.com/JR-1991/Catalax/blob/master/catalax/mcmc/priors.py#L76" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>


Uniform prior distribution.

Represents a uniform distribution between low and high values.


### `LogUniform` <sup><a href="https://github.com/JR-1991/Catalax/blob/master/catalax/mcmc/priors.py#L100" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>


Log-Uniform prior distribution.

Represents a distribution that is uniform in log space.

