JOURNAL ARTICLE

Shrinkage Difference-Based Liu Estimators In Semiparametric Linear Models

Hadi EmamiSara Kiani

Year: 2018 Journal:   Statistics Optimization & Information Computing Vol: 6 (3)   Publisher: International Academic Press

Abstract

<span class="fontstyle0">In this article, under a multicollinearity setting, we define difference-based Liu and non-Liu type shrinkage estimators along with their positive parts in the semiparametric linear model, when the errors are dependent and some nonstochastic linear restrictions are imposed. We derive the biases and exact risk expressions of these estimators and obtain the region of optimality of each estimator. Also, necessary and sufficient conditions, for the superiority of the difference-based Liu estimator over its counterpart, for choosing the Liu parameter </span><span class="fontstyle2">d </span><span class="fontstyle0">are established. Finally, we illustrate the performance of these estimators with a simulation study.</span>

Keywords:
Estimator Multicollinearity Mathematics Semiparametric model Shrinkage Applied mathematics Linear model Shrinkage estimator Linear regression Econometrics Statistics Minimax estimator Minimum-variance unbiased estimator

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4
Cited By
0.94
FWCI (Field Weighted Citation Impact)
25
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0.73
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Citation History

Topics

Statistical Distribution Estimation and Applications
Physical Sciences →  Mathematics →  Statistics and Probability
Advanced Statistical Methods and Models
Physical Sciences →  Mathematics →  Statistics and Probability
Statistical Methods and Inference
Physical Sciences →  Mathematics →  Statistics and Probability

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