https://github.com/computorg/published-202507-jacques-count-data

Model-Based Clustering and Variable Selection for Multivariate Count Data
https://github.com/computorg/published-202507-jacques-count-data

count-data model-based-clustering variable-selection

Last synced: about 11 hours ago
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Model-Based Clustering and Variable Selection for Multivariate Count Data

• Host: GitHub
• URL: https://github.com/computorg/published-202507-jacques-count-data
• Owner: computorg
• License: cc-by-4.0
• Created: 2024-09-30T12:46:56.000Z (almost 2 years ago)
• Default Branch: main
• Last Pushed: 2026-07-07T13:07:28.000Z (1 day ago)
• Last Synced: 2026-07-08T08:04:13.346Z (about 11 hours ago)
• Topics: count-data, model-based-clustering, variable-selection
• Language: TeX
• Homepage: https://computo-journal.org/published-202507-jacques-count-data/
• Size: 1.41 MB
• Stars: 1
• Watchers: 2
• Forks: 3
• Open Issues: 3
• Metadata Files:
  • Readme: README.md

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README

          
# Model-Based Clustering and Variable Selection for Multivariate Count Data

Julien Jacques, Thomas Brendan Murphy

2025-07-01

### Citation

Julien Jacques and Thomas Brendan Murphy (July 2025). Model-Based Clustering and Variable Selection for Multivariate Count Data. Computo.

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### Authors’ affiliations

- Julien Jacques (Université Lumière Lyon 2, Universite Claude Bernard Lyon 1, ERIC, 69007, Lyon, France)

- Thomas Brendan Murphy (School of Mathematics & Statistics, University College Dublin, Institut d’Études Avancées, Université de Lyon)

### Abstract

Model-based clustering provides a principled way of developing

clustering methods. We develop a new model-based clustering methods for

count data. The method combines clustering and variable selection for

improved clustering. The method is based on conditionally independent

Poisson mixture models and Poisson generalized linear models. The method

is demonstrated on simulated data and data from an ultra running race,

where the method yields excellent clustering and variable selection

performance.