Publisher's Synopsis
There has been a rapidly growing interest in Bayesian methods among insurance practitioners in recent years, mainly because of their ability to generate predictive distributions and to rigorously incorporate expert opinion through prior probabilities. This book introduces modern Bayesian modeling techniques for actuarial and insurance applications. It first provides the necessary background in current actuarial practice and then presents Bayesian methods and MCMC. It includes advanced techniques, such as nonlinear modeling, as well as three chapters on model selection and averaging. The text features case studies using real actuarial and insurance data with computations in R and WinBUGS.
