CHRISTOPHER FALLAIZE Chris.Fallaize@nottingham.ac.uk
Lecturer
Bayesian Model Choice for Directional Data
Fallaize, Christopher J.; Kypraios, Theodore
Authors
Dr THEODORE KYPRAIOS THEODORE.KYPRAIOS@NOTTINGHAM.AC.UK
Professor of Statistics
Abstract
This article is concerned with the problem of choosing between competing models for directional data. In particular, we consider the question of whether or not two independent samples of axial data come from the same Bingham distribution. This is not a straightforward question to answer, due to the intractable nature of the parameter-dependent normalizing constant of the Bingham distribution. We propose three different methods to perform this task within a Bayesian framework, and apply the methodology to a real dataset on earthquakes in New Zealand. R code to run our methods is available in online supplementary materials.
Citation
Fallaize, C. J., & Kypraios, T. (2024). Bayesian Model Choice for Directional Data. Journal of Computational and Graphical Statistics, 33(1), 25-34. https://doi.org/10.1080/10618600.2023.2206076
Journal Article Type | Article |
---|---|
Acceptance Date | Apr 16, 2023 |
Online Publication Date | Jun 13, 2023 |
Publication Date | 2024 |
Deposit Date | May 17, 2023 |
Publicly Available Date | Mar 28, 2024 |
Journal | Journal of Computational and Graphical Statistics |
Print ISSN | 1061-8600 |
Electronic ISSN | 1537-2715 |
Publisher | Taylor and Francis |
Peer Reviewed | Peer Reviewed |
Volume | 33 |
Issue | 1 |
Pages | 25-34 |
DOI | https://doi.org/10.1080/10618600.2023.2206076 |
Keywords | Bingham distribution; doubly intractable distributions; model choice; reversible jump MCMC |
Public URL | https://nottingham-repository.worktribe.com/output/19785102 |
Publisher URL | https://www.tandfonline.com/doi/full/10.1080/10618600.2023.2206076 |
Files
Bayesian Model Choice for Directional Data
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