13Bayesian Estimation

All of the previous discussion on estimation has assumed a frequentist approach. That is, the population distribution has been fixed but unknown, and our decisions have been concerned not only with the sample we obtained from the population, but also with the possibilities attached to other samples that might have been obtained. The Bayesian approach assumes that only the data actually observed are relevant and it is the population distribution that is variable. For parameter estimation, the following definitions describe the process and then Bayes' theorem provides the solution.

13.1 Definitions and Bayes' Theorem

As before, the parameter img may be scalar or vector valued. Determination of the prior distribution has always been one of the barriers to the widespread acceptance of Bayesian methods. It is almost certainly the case that your experience has provided some insights about possible parameter values before ...

Get Loss Models, 5th Edition now with the O’Reilly learning platform.

O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.