Go to  Advanced Search

Bayesian cross-validation choice and assessment of statistical models

Show full item record

Files in this item

Files Size Format Description   View
ubc_1999-0455.pdf 2.983Mb Adobe Portable Document Format   View/Open
Title: Bayesian cross-validation choice and assessment of statistical models
Author: Alqallaf, Fatemah Ali
Degree Master of Science - MSc
Program Statistics
Copyright Date: 1999
Abstract: This thesis will be concerned with application of a cross-validation criterion to the choice and assessment of statistical models, in which observed data are partitioned, with one part of the data compared to predictions conditional on the model and the rest of the data. We develop three methods, gold, silver, and bronze based on the idea of splitting data in the context of measuring prediction error; however, they can also be adapted for model checking. The gold method uses analytic calculations for the posterior predictive distribution; however, the silver method avoids this mathematical intensity, instead simulating many posterior samples, and the bronze method reduces the amount of sampling to speed up computation. We also consider the Bayesian p-value in which the posterior distribution can be used to check model adequacy, in the context of cross-validation with repeated data splitting. Application to examples is detailed, using the discussed methodologies of estimation and prediction.
URI: http://hdl.handle.net/2429/9397
Series/Report no. UBC Retrospective Theses Digitization Project [http://www.library.ubc.ca/archives/retro_theses/]

This item appears in the following Collection(s)

Show full item record

All items in cIRcle are protected by copyright, with all rights reserved.

UBC Library
1961 East Mall
Vancouver, B.C.
Canada V6T 1Z1
Tel: 604-822-6375
Fax: 604-822-3893