A Generalization of the Savage–Dickey Density Ratio for Testing Equality and Order Constrained Hypotheses
Joris Mulder,
Eric-Jan Wagenmakers and
Maarten Marsman
The American Statistician, 2022, vol. 76, issue 2, 102-109
Abstract:
The Savage–Dickey density ratio is a specific expression of the Bayes factor when testing a precise (equality constrained) hypothesis against an unrestricted alternative. The expression greatly simplifies the computation of the Bayes factor at the cost of assuming a specific form of the prior under the precise hypothesis as a function of the unrestricted prior. A generalization was proposed by Verdinelli and Wasserman such that the priors can be freely specified under both hypotheses while keeping the computational advantage. This article presents an extension of this generalization when the hypothesis has equality as well as order constraints on the parameters of interest. The methodology is used for a constrained multivariate t-test using the JZS Bayes factor and a constrained hypothesis test under the multinomial model.
Date: 2022
References: Add references at CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://hdl.handle.net/10.1080/00031305.2020.1799861 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:amstat:v:76:y:2022:i:2:p:102-109
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/UTAS20
DOI: 10.1080/00031305.2020.1799861
Access Statistics for this article
The American Statistician is currently edited by Eric Sampson
More articles in The American Statistician from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().