Efficient two-parameter estimator in linear regression model

Ashok V. Dorugade

doi:10.21307/stattrans-2019-021

Efficient two-parameter estimator in linear regression model

Ashok V. Dorugade Y C Mahavidyalaya Halkarni, Tal-Chandgad, Kolhapur, Maharashtra India Statistics in Transition new series, vol. 20, 2019, 2, pages: 173-185 Published online: 2 July 2019 DOI 10.21307/stattrans-2019-021

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ABSTRACT

In this article, two-parameter estimators in linear model with multicollinearity are considered. An alternative efficient two-parameter estimator is proposed and its properties are examined. Furthermore, this was compared with the ordinary least squares (OLS) estimator and ordinary ridge regression (ORR) estimators. Also, using the mean squares error criterion the proposed estimator performs more efficiently than OLS estimator, ORR estimator and other reviewed two-parameter estimators. A numerical example and simulation study are finally conducted to illustrate the superiority of the proposed estimator.

KEYWORDS

multicollinearity, ridge regression, two-parameter estimator, mean squared error

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