Please use this identifier to cite or link to this item: https://ir.iimcal.ac.in:8443/jspui/handle/123456789/1209
Title: Data-dependent probability matching priors for likelihood ratio and adjusted likelihood ratio statistics
Authors: Chang, Inhong
Mukerjee, Rahul
Keywords: Expected information
Highest posterior density region
Observed information
Posterior characteristic function
Shrinkage argument
Issue Date: 2013
Publisher: SCOPUS
Statistics
Series/Report no.: 47(2)
Abstract: We consider likelihood ratio statistics based on the usual profile likelihood and the standard adjustments thereof proposed in the literature in the presence of nuisance parameters. The role of data-dependent priors in ensuring approximate frequentist validity of posterior credible regions based on the inversion of these statistics is investigated. Unlike what happens with data-free priors, it is seen that the resulting probability matching conditions readily admit solutions which entail approximate frequentist validity of the highest posterior density region as well. � 2013 Copyright Taylor and Francis Group, LLC.
Description: Chang, Inhong, Department of Computer Science and Statistics, Chosun University, Gwangju, 501-759, South Korea; Mukerjee, Rahul, Indian Institute of Management Calcutta, Diamond Harbour Road, Joka, Kolkata, 700 104, India
ISSN/ISBN - 02331888
pp.294-305
DOI - 10.1080/02331888.2011.587880
URI: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84876045069&doi=10.1080%2f02331888.2011.587880&partnerID=40&md5=c82246f5cef28abe6b643b73856092ce
https://ir.iimcal.ac.in:8443/jspui/handle/123456789/1209
Appears in Collections:Operations Management

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