2021-10-052021-05-121794-91652256-4314http://hdl.handle.net/10784/30404We study multiple linear regression model under non-normally distributed random error by considering the family of generalized secant hyperbolic distributions. We derive the estimators of model parameters by using modified maximum likelihood methodology and explore the properties of the modified maximum likelihood estimators so obtained. We show that the proposed estimators are more efficient and robust than the commonly used least square estimators. We also develop the relevant test of hypothesis procedures and compared the performance of such tests vis-a-vis the classical tests that are based upon the least square approach.application/pdfengCopyright © 2021 Álvaro Alexander Burbano Moreno, Oscar Orlando Melo-Martinez, M Qamarul Islaminfo:eu-repo/semantics/articleinfo:eu-repo/semantics/openAccessMaximum likelihoodModified maximum likelihoodLeast squareGeneralized Secant Hyperbolic distributionRobustnessHypothesis testingAcceso abierto2021-10-05Burbano Moreno, Álvaro AlexanderMelo-Martinez, Oscar OrlandoQamarul Islam, M