Robust Bayesian hypothesis testing in the presence of nuisance parameters

Published

Journal Article

Robust Bayesian testing of point null hypotheses is considered for problems involving the presence of nuisance parameters. The robust Bayesian approach seeks answers that hold for a range of prior distributions. Three techniques for handling the nuisance parameter are studied and compared. They are (i) utilize a noninformative prior to integrate out the nuisance parameter; (ii) utilize a test statistic whose distribution does not depend on the nuisance parameter; and (iii) use a class of prior distributions for the nuisance parameter. These approaches are studied in two examples, the univariate normal model with unknown mean and variance, and a multivariate normal example. © 1994.

Full Text

Duke Authors

Cited Authors

  • Berger, J; Mortera, J

Published Date

  • January 1, 1994

Published In

Volume / Issue

  • 40 / 2-3

Start / End Page

  • 357 - 373

International Standard Serial Number (ISSN)

  • 0378-3758

Digital Object Identifier (DOI)

  • 10.1016/0378-3758(94)90131-7

Citation Source

  • Scopus