Implementation of Gibbs Sampling within Bayesian Inference and its Applications in Actuarial Science

Abstract

This paper discusses how a variety of actuarial models can be implemented and analyzed with a Bayesian approach using Gibbs sampling, a Markov chain Monte Carlo method. This approach allows a practitioner to analyze complicated actuarial models by reducing them to simpler, more manageable models. Furthermore, general properties of Gibbs sampling are discussed through a simulation approach.