EMLM

Name	EMLM JSON
Version	0.1 JSON
	download
home_page	https://github.com/yourusername/EMLM
Summary	A package for Bayesian linear regression with mixture models
upload_time	2024-02-17 12:23:09
maintainer
docs_url	None
author	Your Name
requires_python
license	MIT
keywords
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            #EMLM
EMLM is a Python package for Bayesian linear regression with mixture models.

Overview
EMLM implements a Bayesian approach to linear regression with mixture models, allowing for more flexible and robust modeling of complex data structures. It combines the power of Bayesian inference with the flexibility of mixture models to handle heteroscedasticity, outliers, and other challenging data patterns.

Features
Bayesian linear regression with mixture models
Flexible handling of heteroscedasticity and outliers
Markov Chain Monte Carlo (MCMC) sampling for parameter estimation
Parallelization support for faster computation
Easy-to-use interface for model fitting and inference
Installation
You can install EMLM via pip:
```
pip install EMLM

```






            

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