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Two Kinds of Weighted Biased Estimators in Stochastic Restricted Regression Model

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Listed:
  • Chaolin Liu
  • Haina Jiang
  • Xinhui Shi
  • Donglin Liu

Abstract

We consider two kinds of weighted mixed almost unbiased estimators in a linear stochastic restricted regression model when the prior information and the sample information are not equally important. The superiorities of the two new estimators are discussed according to quadratic bias and variance matrix criteria. Under such criteria, we perform a real data example and a Monte Carlo study to illustrate theoretical results.

Suggested Citation

  • Chaolin Liu & Haina Jiang & Xinhui Shi & Donglin Liu, 2014. "Two Kinds of Weighted Biased Estimators in Stochastic Restricted Regression Model," Journal of Applied Mathematics, John Wiley & Sons, vol. 2014(1).
    • Handle: RePEc:wly:jnljam:v:2014:y:2014:i:1:n:314875
    DOI: 10.1155/2014/314875
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    References listed on IDEAS

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    1. Jibo Wu, 2013. "On the Performance of Principal Component Liu-Type Estimator under the Mean Square Error Criterion," Journal of Applied Mathematics, Hindawi, vol. 2013, pages 1-7, December.
    2. 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).
    3. 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.
    4. Jibo Wu, 2013. "On the Performance of Principal Component Liu‐Type Estimator under the Mean Square Error Criterion," Journal of Applied Mathematics, John Wiley & Sons, vol. 2013(1).
    5. Gülesen Üstündagˇ Şiray & Selahattin Kaçıranlar & Sadullah Sakallıoğlu, 2014. "r − k Class estimator in the linear regression model with correlated errors," Statistical Papers, Springer, vol. 55(2), pages 393-407, May.
    6. Kadiyala, Krishna, 1984. "A class of almost unbiased and efficient estimators of regression coefficients," Economics Letters, Elsevier, vol. 16(3-4), pages 293-296.
    7. 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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