Multiple linear regression model under nonnormality

Islam, M. QamarulTiku, Moti L.2024-04-252024-04-252004Islam, M. Qamarul; Tiku, Moti L. (2004). "Multiple linear regression model under nonnormality", Communications in Statistics - Theory and Methods, Vol.33, No.10, pp.2443-2467.3610926http://hdl.handle.net/20.500.12416/7959We 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.eninfo:eu-repo/semantics/closedAccessHypothesis TestingLeast SquaresM EstimatorsModified LikelihoodMultiple Linear RegressionNonnormalityOutliersRobustnessMultiple linear regression model under nonnormalityMultiple linear regression model under nonnormalityArticle33102443246710.1081/STA-200031519