# Posts tagged generalized linear model

## Bayesian regression with truncated or censored data

- 01 September 2022
- Category: beginner

The notebook provides an example of how to conduct linear regression when your outcome variable is either censored or truncated.

## Rolling Regression

- 01 June 2022
- Category: intermediate

Pairs trading is a famous technique in algorithmic trading that plays two stocks against each other.

## GLM: Negative Binomial Regression

- 01 June 2022
- Category: beginner

This notebook closely follows the GLM Poisson regression example by Jonathan Sedar (which is in turn inspired by a project by Ian Osvald) except the data here is negative binomially distributed instead of Poisson distributed.

## NBA Foul Analysis with Item Response Theory

- 17 April 2022
- Category: intermediate, tutorial

This tutorial shows an application of Bayesian Item Response Theory [Fox, 2010] to NBA basketball foul calls data using PyMC. Based on Austin Rochfordâ€™s blogpost NBA Foul Calls and Bayesian Item Response Theory.

## Binomial regression

- 01 February 2022
- Category: beginner

This notebook covers the logic behind Binomial regression, a specific instance of Generalized Linear Modelling. The example is kept very simple, with a single predictor variable.

## GLM: Model Selection

- 08 January 2022
- Category: intermediate

A fairly minimal reproducible example of Model Selection using WAIC, and LOO as currently implemented in PyMC3.

## Hierarchical Binomial Model: Rat Tumor Example

- 11 November 2021
- Category: intermediate

This short tutorial demonstrates how to use PyMC to do inference for the rat tumour example found in chapter 5 of *Bayesian Data Analysis 3rd Edition* [Gelman *et al.*, 2013]. Readers should already be familiar with the PyMC API.

## GLM: Mini-batch ADVI on hierarchical regression model

- 23 September 2021
- Category: intermediate

Unlike Gaussian mixture models, (hierarchical) regression models have independent variables. These variables affect the likelihood function, but are not random variables. When using mini-batch, we should take care of that.