A Bayesian hierarchical model for criminal investigations

DOI10.1214/19-BA1192zbMath1480.62113arXiv1907.01894MaRDI QIDQ2057365

F. O. Bunnin, James Q. Smith

Publication date: 6 December 2021

Published in: Bayesian Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1907.01894

zbMATH Keywords

decision support systemsMarkov processesMarkov switching modelsprobabilistic graphical modelshierarchical modelschain event graphs

Mathematics Subject Classification ID

Applications of statistics to social sciences (62P25) Bayesian inference (62F15) Markov processes: hypothesis testing (62M02) Probabilistic graphical models (62H22)

Cites Work

• Unnamed Item
• The dynamic chain event graph
• A new family of non-local priors for chain event graph model selection
• Bayesian forecasting and dynamic models.
• Chain event graphs for informed missingness
• Modeling and estimation for self-exciting spatio-temporal models of terrorist activity
• Equivalence classes of staged trees
• Refining a Bayesian network using a chain event graph
• Finite mixture and Markov switching models.
• Causal discovery through MAP selection of stratified chain event graphs
• Bayesian Decision Analysis
• Inference and missing data
• Statistics and the Evaluation of Evidence for Forensic Scientists
• Uncertain Judgements: Eliciting Experts' Probabilities

This page was built for publication: A Bayesian hierarchical model for criminal investigations