Bayesian mixture models in a longitudinal setting for analysing sheep CAT scan images

DOI10.1016/j.csda.2006.05.013zbMath1162.62428OpenAlexW2060269508WikidataQ56994587 ScholiaQ56994587MaRDI QIDQ1020083

J. Martínez

Publication date: 29 May 2009

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2006.05.013

zbMATH Keywords

Markov chain Monte Carlodensity estimationMarkov random fieldGibbs samplingmetropolis-hastings algorithmperturbation parametersposterior simulation

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15)

Related Items (3)

Using informative priors in the estimation of mixtures over time with application to aerosol particle size distributions ⋮ An external field prior for the hidden Potts model with application to cone-beam computed tomography ⋮ Scalable Bayesian inference for the inverse temperature of a hidden Potts model

Uses Software

• CODA
• CATMAN

Cites Work

• Bayesian analysis of mixture models with an unknown number of components\,--\,an alternative to reversible jump methods.
• Estimators of Tissue Proportions from X-Ray CT Images
• Finite mixture models
• Bayes Factors
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