Statistical Inference for Branching Processes

Using one of the simplest possible cases, this book illustrates the problems of statistical inference that can arise when the standard assumption of independent observations is relaxed. It contains observations on the generation sizes of a Bienayme-Galton-Watson process. In addition, problems of conditional inference and ancilliarity in stochastic processes are presented in this context, both for estimation and testing problems. Throughout the book, theoretical results are illustrated in special cases and scientific applications of the theory and method are presented. A chapter has been devoted to Bayesian methods of inference.