A Practical Procedure to Find Matching Priors for Frequentist Inference

We present a practical way to find matching priors via the use of saddlepoint approximations and obtain p-values of tests of an interest parameter in the presence of nuisance parameters. The advantages of our procedure are the flexibility in choosing different initial conditions so that one may adju...

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Bibliographic Details
Published inCommunications in statistics. Theory and methods Vol. 42; no. 15; pp. 2758 - 2767
Main Authors Zhang, Juan, Kolassa, John E.
Format Journal Article
LanguageEnglish
Published Philadelphia Taylor & Francis Group 03.08.2013
Taylor & Francis Ltd
Subjects
Adjustment
Approximation
Bayes
Computation
Conditional inference
Flexibility
Initial conditions
Matching
Matching prior
Modified signed root likelihood ratio statistic
Nuisance
Partial differential equation
Partial differential equations
Primary 62E20
Saddlepoint approximation
Secondary 62C10
Statistics
Studies
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Summary:We present a practical way to find matching priors via the use of saddlepoint approximations and obtain p-values of tests of an interest parameter in the presence of nuisance parameters. The advantages of our procedure are the flexibility in choosing different initial conditions so that one may adjust the performance of a test, and the less intensive computational efforts compared to a Markov Chain Monto Carlo method.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0361-0926
1532-415X
DOI:10.1080/03610926.2011.617479