MSE performance of the weighted average estimators consisting of shrinkage estimators

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Abstract

In this paper, we consider a regression model and propose estimators which are the weighted averages of two estimators among three estimators; the Stein-rule (SR), the minimum mean squared error (MMSE), and the adjusted minimum mean-squared error (AMMSE) estimators. It is shown that one of the proposed estimators has smaller mean-squared error (MSE) than the positive-part Stein-rule (PSR) estimator over a moderate region of parameter space when the number of the regression coefficients is small (i.e., 3), and its MSE performance is comparable to the PSR estimator even when the number of the regression coefficients is not so small.

Journal

  • Communications in Statistics-Theory and Methods

    Communications in Statistics-Theory and Methods 47(5), 1204-1214, 2018

    Taylor & Francis

Codes

  • NII Article ID (NAID)
    120006477538
  • Text Lang
    ENG
  • Article Type
    journal article
  • ISSN
    0361-0926
  • Data Source
    IR 
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