Estimation in a linear regression model with stochastic linear restrictions: a new two-parameter-weighted mixed estimator |
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Authors: | Nimet Özbay Selahattin Kaç?ranlar |
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Institution: | 1. Department of Statistics, Faculty of Science and Letters, ?ukurova University, Adana, Turkeynturker@cu.edu.tr;3. Department of Statistics, Faculty of Science and Letters, ?ukurova University, Adana, Turkey |
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Abstract: | The present paper considers the weighted mixed regression estimation of the coefficient vector in a linear regression model with stochastic linear restrictions binding the regression coefficients. We introduce a new two-parameter-weighted mixed estimator (TPWME) by unifying the weighted mixed estimator of Schaffrin and Toutenburg 1] and the two-parameter estimator (TPE) of Özkale and Kaç?ranlar 2]. This new estimator is a general estimator which includes the weighted mixed estimator, the TPE and the restricted two-parameter estimator (RTPE) proposed by Özkale and Kaç?ranlar 2] as special cases. Furthermore, we compare the TPWME with the weighted mixed estimator and the TPE with respect to the matrix mean square error criterion. A numerical example and a Monte Carlo simulation experiment are presented by using different estimators of the biasing parameters to illustrate some of the theoretical results. |
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Keywords: | Stochastic linear restrictions two-parameter estimator two-parameter-weighted mixed estimator weighted mixed estimator |
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