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Multiple Linear Regression Model Under Nonnormality

dc.contributor.author Islam, MQ
dc.contributor.author Tiku, ML
dc.contributor.other 01. Çankaya Üniversitesi
dc.date.accessioned 2021-12-14T10:39:11Z
dc.date.accessioned 2025-09-18T15:43:48Z
dc.date.available 2021-12-14T10:39:11Z
dc.date.available 2025-09-18T15:43:48Z
dc.date.issued 2004
dc.description.abstract We consider multiple linear regression models under nonnormality. We derive modified maximum likelihood estimators (MMLEs) of the parameters and show that they are efficient and robust. We show that the least squares esimators are considerably less efficient. We compare the efficiencies of the MMLEs and the M estimators for symmetric distributions and show that, for plausible alternatives to an assumed distribution, the former are more efficient. We provide real-life examples. en_US
dc.description.publishedMonth 10
dc.identifier.citation Islam, M. Q.; Tiku, M. L. (2004). "Multiple linear regression model under nonnormality", Communications in Statistics-Theory and Methods, Vol. 33, No. 10, pp. 2443-2467 en_US
dc.identifier.doi 10.1081/STA-200031519
dc.identifier.issn 0361-0926
dc.identifier.issn 1532-415X
dc.identifier.scopus 2-s2.0-9944238858
dc.identifier.uri https://doi.org/10.1081/STA-200031519
dc.identifier.uri https://hdl.handle.net/20.500.12416/14051
dc.language.iso en en_US
dc.publisher Taylor & Francis inc en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.subject Multiple Linear Regression en_US
dc.subject Modified Likelihood en_US
dc.subject Robustness en_US
dc.subject Outliers en_US
dc.subject M Estimators en_US
dc.subject Least Squares en_US
dc.subject Nonnormality en_US
dc.subject Hypothesis Testing en_US
dc.title Multiple Linear Regression Model Under Nonnormality en_US
dc.title Multiple linear regression model under nonnormality tr_TR
dc.type Article en_US
dspace.entity.type Publication
gdc.author.institutional Islam, M.Qamarul
gdc.author.scopusid 55547120879
gdc.author.scopusid 7005739359
gdc.description.department Çankaya University en_US
gdc.description.departmenttemp Cankaya Univ, Dept Econ, TR-06530 Ankara, Turkey; Middle E Tech Univ, Dept Stat, TR-06531 Ankara, Turkey; McMaster Univ, Hamilton, ON L8S 4L8, Canada en_US
gdc.description.endpage 2467 en_US
gdc.description.issue 10 en_US
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality Q2
gdc.description.startpage 2443 en_US
gdc.description.volume 33 en_US
gdc.description.woscitationindex Science Citation Index Expanded
gdc.description.wosquality Q4
gdc.identifier.openalex W1966193234
gdc.identifier.wos WOS:000225384500011
gdc.openalex.fwci 1.78033128
gdc.openalex.normalizedpercentile 0.85
gdc.opencitations.count 48
gdc.plumx.crossrefcites 30
gdc.plumx.mendeley 27
gdc.plumx.scopuscites 64
gdc.scopus.citedcount 64
gdc.wos.citedcount 61
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