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On the Weighted Mixed Almost Unbiased Ridge Estimator in Stochastic Restricted Linear Regression

Author

Listed:
  • Chaolin Liu
  • Hu Yang
  • Jibo Wu

Abstract

We introduce the weighted mixed almost unbiased ridge estimator (WMAURE) based on the weighted mixed estimator (WME) (Trenkler and Toutenburg 1990) and the almost unbiased ridge estimator (AURE) (Akdeniz and Erol 2003) in linear regression model. We discuss superiorities of the new estimator under the quadratic bias (QB) and the mean square error matrix (MSEM) criteria. Additionally, we give a method about how to obtain the optimal values of parameters k and w. Finally, theoretical results are illustrated by a real data example and a Monte Carlo study.

Suggested Citation

  • Chaolin Liu & Hu Yang & Jibo Wu, 2013. "On the Weighted Mixed Almost Unbiased Ridge Estimator in Stochastic Restricted Linear Regression," Journal of Applied Mathematics, John Wiley & Sons, vol. 2013(1).
    • Handle: RePEc:wly:jnljam:v:2013:y:2013:i:1:n:902715
    DOI: 10.1155/2013/902715
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    References listed on IDEAS

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    1. Hu Yang & Jianwen Xu, 2009. "An alternative stochastic restricted Liu estimator in linear regression," Statistical Papers, Springer, vol. 50(3), pages 639-647, June.
    2. Yalian Li & Hu Yang, 2010. "A new stochastic mixed ridge estimator in linear regression model," Statistical Papers, Springer, vol. 51(2), pages 315-323, June.
    3. Kadiyala, Krishna, 1984. "A class of almost unbiased and efficient estimators of regression coefficients," Economics Letters, Elsevier, vol. 16(3-4), pages 293-296.
    4. M. Hubert & P. Wijekoon, 2006. "Improvement of the Liu estimator in linear regression model," Statistical Papers, Springer, vol. 47(3), pages 471-479, June.
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    Cited by:

    1. Jibo Wu, 2014. "On the Stochastic Restricted r‐k Class Estimator and Stochastic Restricted r‐d Class Estimator in Linear Regression Model," Journal of Applied Mathematics, John Wiley & Sons, vol. 2014(1).

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