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Likelihood inference for small variance components

Stern, Steven E.; Welsh, A. H.

Description

The authors explore likelihood-based methods for making inferences about the components of variance in a general normal mixed linear model. In particular, they use local asymptotic approximations to construct confidence intervals for the components of variance when the components are close to the boundary of the parameter space. In the process, they explore the question of how to profile the restricted likelihood (REML). Also, they show that general REML estimates are less likely to fall on the...[Show more]

dc.contributor.authorStern, Steven E.
dc.contributor.authorWelsh, A. H.
dc.date.accessioned2002-06-06
dc.date.accessioned2004-05-19T12:01:54Z
dc.date.accessioned2011-01-05T08:37:19Z
dc.date.available2004-05-19T12:01:54Z
dc.date.available2011-01-05T08:37:19Z
dc.date.created2000
dc.identifier.issn0319-5724
dc.identifier.urihttp://hdl.handle.net/1885/40704
dc.description.abstractThe authors explore likelihood-based methods for making inferences about the components of variance in a general normal mixed linear model. In particular, they use local asymptotic approximations to construct confidence intervals for the components of variance when the components are close to the boundary of the parameter space. In the process, they explore the question of how to profile the restricted likelihood (REML). Also, they show that general REML estimates are less likely to fall on the boundary of the parameter space than maximum likelihood estimates and that the likelihood ratio test based on the local asymptotic approximation has higher power than the likelihood ratio test based on the usual chi-squared approximation. They examine the finite sample properties of the proposed intervals by means of a simulation study.
dc.format.extent206647 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen_AU
dc.publisherStatistical Society of Canada
dc.sourceCanadian Journal of Statistics
dc.subjectboundary
dc.subjectlikelihood-based inference
dc.subjectlocal asymptotics
dc.subjectmaximum likelihood estimation
dc.subjectREML
dc.subjectvariance components
dc.subjectWald test
dc.titleLikelihood inference for small variance components
dc.typeWorking/Technical Paper
local.description.refereedno
local.identifier.citationvolume28
local.identifier.citationyear2000
local.identifier.eprintid417
local.rights.ispublishedyes
local.identifier.absfor020204 - Plasma Physics; Fusion Plasmas; Electrical Discharges
local.identifier.ariespublicationMigratedxPub18672
local.type.statusPublished Version
local.contributor.affiliationANU
local.contributor.affiliationSchool of Finance and Applied Statistics
local.citationResearch Papers in Statistics 2000-01
local.bibliographicCitation.issue3
local.bibliographicCitation.startpage517
local.bibliographicCitation.lastpage532
dc.date.updated2015-12-12T08:40:45Z
local.identifier.scopusID2-s2.0-0034362615
CollectionsANU Research Publications

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