Posts by Oriol Abril-Pla

Model building and expansion for golf putting

This uses and closely follows the case study from Andrew Gelman, written in Stan. There are some new visualizations and we steered away from using improper priors, but much credit to him and to the Stan group for the wonderful case study and software.

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Factor analysis

Factor analysis is a widely used probabilistic model for identifying low-rank structure in multivariate data as encoded in latent variables. It is very closely related to principal components analysis, and differs only in the prior distributions assumed for these latent variables. It is also a good example of a linear Gaussian model as it can be described entirely as a linear transformation of underlying Gaussian variates. For a high-level view of how factor analysis relates to other models, you can check out this diagram originally published by Ghahramani and Roweis.

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A Hierarchical model for Rugby prediction

In this example, we’re going to reproduce the first model described in Baio and Blangiardo [2010] using PyMC. Then show how to sample from the posterior predictive to simulate championship outcomes from the scored goals which are the modeled quantities.

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GLM: Model Selection

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

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Dirichlet mixtures of multinomials

This example notebook demonstrates the use of a Dirichlet mixture of multinomials (a.k.a Dirichlet-multinomial or DM) to model categorical count data. Models like this one are important in a variety of areas, including natural language processing, ecology, bioinformatics, and more.

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