A simple analysis of the exact probability matching prior in the location-scale model
Author(s)
DiCiccio, TJ
Kuffner, TA
Young, GA
Type
Journal Article
Abstract
It has long been asserted that in univariate location-scale models, when concerned with inference for either the location or scale parameter, the use of the inverse of the scale parameter as a Bayesian prior yields posterior credible sets which have exactly the correct frequentist confidence set interpretation. This claim dates to at least Peers (1965), and has subsequently been noted by various authors, with varying degrees of justification. We present a simple, direct demonstration of the exact matching property of the posterior credible sets derived under use of this prior in the univariate location-scale model. This is done by establishing an equivalence between the conditional frequentist and posterior densities of the pivotal quantities on which conditional frequentist inferences are based.
Date Issued
2017-06-29
Date Acceptance
2016-10-25
Citation
The American statistician, 2017, 71 (4), pp.302-304
ISSN
1537-2731
Publisher
Taylor & Francis
Start Page
302
End Page
304
Journal / Book Title
The American statistician
Volume
71
Issue
4
Copyright Statement
This is an Accepted Manuscript of an article published by Taylor & Francis Group in The American statisticianon 29 June 2017 available online at: http://www.tandfonline.com/10.1080/00031305.2016.1255662
Subjects
Science & Technology
Physical Sciences
Statistics & Probability
Mathematics
Conditional inference
Location-scale
Matching prior
Objective Bayes
p*
LIKELIHOOD
PARAMETERS
0104 Statistics
Notes
peerreview_statement: The publishing and review policy for this title is described in its Aims & Scope. aims_and_scope_url: http://www.tandfonline.com/action/journalInformation?show=aimsScope&journalCode=utas20
Publication Status
Published
Date Publish Online
2016-12-15