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On the Stochastic Restricted Modified Almost Unbiased Liu Estimator in Linear Regression Model

On the Stochastic Restricted Modified Almost Unbiased Liu Estimator in Linear Regression Model In this article, we propose a new biased estimator, namely stochastic restricted modified almost unbiased Liu estimator by combining modified almost unbiased Liu estimator (MAULE) and mixed estimator (ME) when the stochastic restrictions are available and the multicollinearity presents. The conditions of superiority of the proposed estimator over the ordinary least square estimator, ME, ridge estimator, Liu estimator, almost unbiased Liu estimator, stochastic restricted Liu estimator and MAULE in the mean squared error matrix sense are obtained. Finally, a numerical example and a Monte Carlo simulation are given to illustrate the theoretical findings. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Communications in Mathematics and Statistics Springer Journals

On the Stochastic Restricted Modified Almost Unbiased Liu Estimator in Linear Regression Model

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Publisher
Springer Journals
Copyright
Copyright © 2018 by School of Mathematical Sciences, University of Science and Technology of China and Springer-Verlag GmbH Germany, part of Springer Nature
Subject
Mathematics; Mathematics, general; Statistics, general
ISSN
2194-6701
eISSN
2194-671X
DOI
10.1007/s40304-018-0131-3
Publisher site
See Article on Publisher Site

Abstract

In this article, we propose a new biased estimator, namely stochastic restricted modified almost unbiased Liu estimator by combining modified almost unbiased Liu estimator (MAULE) and mixed estimator (ME) when the stochastic restrictions are available and the multicollinearity presents. The conditions of superiority of the proposed estimator over the ordinary least square estimator, ME, ridge estimator, Liu estimator, almost unbiased Liu estimator, stochastic restricted Liu estimator and MAULE in the mean squared error matrix sense are obtained. Finally, a numerical example and a Monte Carlo simulation are given to illustrate the theoretical findings.

Journal

Communications in Mathematics and Statistics – Springer Journals

Published: Apr 30, 2018

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