Mean loglikelihood and higher-order approximations
Higher-order approximations to p-values can be obtained from the loglikelihood function and a reparameterization that can be viewed as a canonical parameter in an exponential family approximation to the model. This approach clarifies the connection between Skovgaard (1996) and Fraser et al. (1999a),...
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Veröffentlicht in: | Biometrika 2010-03, Vol.97 (1), p.159-170 |
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container_title | Biometrika |
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creator | Reid, N. Fraser, D. A. S. |
description | Higher-order approximations to p-values can be obtained from the loglikelihood function and a reparameterization that can be viewed as a canonical parameter in an exponential family approximation to the model. This approach clarifies the connection between Skovgaard (1996) and Fraser et al. (1999a), and shows that the Skovgaard approximation can be obtained directly using the mean loglikelihood function. |
doi_str_mv | 10.1093/biomet/asq001 |
format | Article |
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A. S.</creatorcontrib><title>Mean loglikelihood and higher-order approximations</title><title>Biometrika</title><description>Higher-order approximations to p-values can be obtained from the loglikelihood function and a reparameterization that can be viewed as a canonical parameter in an exponential family approximation to the model. This approach clarifies the connection between Skovgaard (1996) and Fraser et al. 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S.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c526t-ed39d0c1d82ac22ba4c1af549b89008c9612ba7d160a4146a3846b63d01ca1b83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Applications</topic><topic>Approximate pivot</topic><topic>Approximation</topic><topic>Biology, psychology, social sciences</topic><topic>Coordinate systems</topic><topic>Exact sciences and technology</topic><topic>Fraser information</topic><topic>General topics</topic><topic>Inference</topic><topic>Kullback–Leibler distance</topic><topic>Mathematical independent variables</topic><topic>Mathematical models</topic><topic>Mathematical vectors</topic><topic>Mathematics</topic><topic>p approximation</topic><topic>Parameter estimation</topic><topic>Parametric models</topic><topic>Probability and statistics</topic><topic>Scalars</topic><topic>Sciences and techniques of general use</topic><topic>Statistics</topic><topic>Studies</topic><topic>Tangent exponential model</topic><topic>Tangent function</topic><topic>Tangents</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Reid, N.</creatorcontrib><creatorcontrib>Fraser, D. 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S.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Mean loglikelihood and higher-order approximations</atitle><jtitle>Biometrika</jtitle><date>2010-03-01</date><risdate>2010</risdate><volume>97</volume><issue>1</issue><spage>159</spage><epage>170</epage><pages>159-170</pages><issn>0006-3444</issn><issn>1464-3510</issn><eissn>1464-3510</eissn><eissn>0006-3444</eissn><coden>BIOKAX</coden><abstract>Higher-order approximations to p-values can be obtained from the loglikelihood function and a reparameterization that can be viewed as a canonical parameter in an exponential family approximation to the model. This approach clarifies the connection between Skovgaard (1996) and Fraser et al. (1999a), and shows that the Skovgaard approximation can be obtained directly using the mean loglikelihood function.</abstract><cop>Oxford</cop><pub>Oxford University Press</pub><doi>10.1093/biomet/asq001</doi><tpages>12</tpages><oa>free_for_read</oa></addata></record> |
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source | Jstor Complete Legacy; Oxford University Press Journals All Titles (1996-Current); RePEc; Alma/SFX Local Collection; JSTOR Mathematics & Statistics |
subjects | Applications Approximate pivot Approximation Biology, psychology, social sciences Coordinate systems Exact sciences and technology Fraser information General topics Inference Kullback–Leibler distance Mathematical independent variables Mathematical models Mathematical vectors Mathematics p approximation Parameter estimation Parametric models Probability and statistics Scalars Sciences and techniques of general use Statistics Studies Tangent exponential model Tangent function Tangents |
title | Mean loglikelihood and higher-order approximations |
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