Posts tagged generalized linear model

NBA Foul Analysis with Item Response Theory

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

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Binomial regression

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.

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Bayesian regression with truncated or censored data

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

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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 [Gelman et al., 2013]. Readers should already be familliar with the PyMC3 API.

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GLM: Mini-batch ADVI on hierarchical regression model

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.

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Rolling Regression

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

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