Applying Reversible Jump MCMC to Bayesian model of crime and punishment in England, with reference to the Old Bailey Courthouse.

Type of content
Theses / Dissertations
Publisher's DOI/URI
Thesis discipline
Statistics
Degree name
Master of Science
Publisher
University of Canterbury
Journal Title
Journal ISSN
Volume Title
Language
English
Date
2020
Authors
Shields, Julianne
Abstract

In this thesis, we have used the Reversible Jump MCMC algorithm to model annual counts of various crimes committed and punishments meted out based on the trial records of the Old Bailey Courthouse in London over the period of 1674 – 1913. A total of 223,248 cases were heard over the 240 years. Our Bayesian model allows us to estimate not only the average frequencies of various crimes and punishments over the years, but also do identify points of abrupt changes, which may have been due to changes in legislation, societal norms or economic situations. We proffer a possible explanation for some of these findings and explain their relevancy to our times.

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Citation
Keywords
Ngā upoko tukutuku/Māori subject headings
ANZSRC fields of research
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All Right Reserved