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A novel AIC variant for linear regression models based on a bootstrap correction

Seghouane, Abd-Krim

Description

The Akaike information criterion, AIC, and its corrected version, AIC c are two methods for selecting normal linear regression models. Both criteria were designed as estimators of the expected Kullback-Leibler information between the model generating the

dc.contributor.authorSeghouane, Abd-Krim
dc.coverage.spatialCancun Mexico
dc.date.accessioned2015-12-10T22:14:09Z
dc.date.createdOctober 16-19 2008
dc.identifier.isbn9781424423750
dc.identifier.urihttp://hdl.handle.net/1885/50143
dc.description.abstractThe Akaike information criterion, AIC, and its corrected version, AIC c are two methods for selecting normal linear regression models. Both criteria were designed as estimators of the expected Kullback-Leibler information between the model generating the
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE Inc)
dc.relation.ispartofseriesIEEE Workshop on Machine Learning for Signal Processing 2008
dc.sourceProceedings of IEEE Workshop on Machine Learning for Signal Processing 2008
dc.subjectKeywords: Akaike Information criterions; Asymptotic approximations; Candidate models; Linear regression models; Polynomial regressions; Simulation results; Small samples; Asymptotic analysis; Learning systems; Linear regression; Polynomial approximation; Regression
dc.titleA novel AIC variant for linear regression models based on a bootstrap correction
dc.typeConference paper
local.description.notesImported from ARIES
local.description.refereedYes
dc.date.issued2008
local.identifier.absfor090609 - Signal Processing
local.identifier.absfor010405 - Statistical Theory
local.identifier.ariespublicationu4334215xPUB198
local.type.statusPublished Version
local.contributor.affiliationSeghouane, Abd-Krim, College of Engineering and Computer Science, ANU
local.description.embargo2037-12-31
local.bibliographicCitation.startpage139
local.bibliographicCitation.lastpage144
local.identifier.doi10.1109/MLSP.2008.4685469
dc.date.updated2016-02-24T10:59:02Z
local.identifier.scopusID2-s2.0-58049139196
CollectionsANU Research Publications

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