Applying Reversible Jump MCMC to Bayesian model of crime and punishment in England, with reference to the Old Bailey Courthouse. (2020)
Type of ContentElectronic Thesis or Dissertation
Degree NameMaster of Science
PublisherUniversity of Canterbury
AuthorsShields, Julianneshow all
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.