Abstract
In this last chapter of the book, we discuss several other related Monte Carlo methods commonly used in Bayesian computation. More specifically, we present various Bayesian methods for model adequacy and related computational techniques, including Monte Carlo estimation of Conditional Predictive Ordinates (CPO) and various Bayesian residuals. This chapter also provides a detailed treatment of the computation of posterior modes, and sampling from posterior distributions for proportional hazards models and mixture of Dirichlet process models.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2000 Springer Science+Business Media New York
About this chapter
Cite this chapter
Chen, MH., Shao, QM., Ibrahim, J.G. (2000). Other Topics. In: Monte Carlo Methods in Bayesian Computation. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-1276-8_10
Download citation
DOI: https://doi.org/10.1007/978-1-4612-1276-8_10
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4612-7074-4
Online ISBN: 978-1-4612-1276-8
eBook Packages: Springer Book Archive