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Communications in Statistics - Simulation and Computation Volume 51, 2022 - Issue 6
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Original Articles

Another proposal about the new two-parameter estimator for linear regression model with correlated regressors

Shakeel AhmadDepartment of Statistics, Bahauddin Zakariya University, Multan, Pakistan
&
Muhammad AslamDepartment of Statistics, Bahauddin Zakariya University, Multan, PakistanCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0003-2290-2307
ORCID Icon
Pages 3054-3072 | Received 07 Aug 2019, Accepted 12 Dec 2019, Published online: 07 Jan 2020
 
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Abstract

In this article, we present a new general class of biased estimators which includes some popular estimators as special cases and discuss its properties for multiple linear regression models when regressors are correlated. This proposal is based on some modification in the existing new two-parameter estimator. Performance of the proposed estimator is compared with many of the leading estimators, using the mean squared error matrix criterion, mitigating the adverse effects of multicollinearity. An extensive simulation study has been provided with a numerical example to illustrate the superiority of the proposed estimator.

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