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Generalized ridge shrinkage estimation in restricted linear model

Author

Listed:
  • Feng Qian

    (Changzhou Institute of Technology)

  • Rong Chen

    (Beijing University of Technology)

  • Ling Wang

    (Nanjing Vocational University of Industry Technology)

Abstract

In the case of multicollinearity, biased estimators are always introduced to correct the least squares estimator. In this paper, we propose a new biased estimator for the restricted linear model. The properties of the new estimator and its superiority over the restricted least squares estimator in terms of the mean square error and Pitman closeness criterion are theoretically analysed. Furthermore, we optimize and verify the feasibility of the new estimator using a numerical simulation.

Suggested Citation

  • Feng Qian & Rong Chen & Ling Wang, 2024. "Generalized ridge shrinkage estimation in restricted linear model," Computational Statistics, Springer, vol. 39(3), pages 1403-1416, May.
    • Handle: RePEc:spr:compst:v:39:y:2024:i:3:d:10.1007_s00180-023-01357-1
    DOI: 10.1007/s00180-023-01357-1
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    References listed on IDEAS

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    1. Hawkins, Douglas M. & Yin, Xiangrong, 2002. "A faster algorithm for ridge regression of reduced rank data," Computational Statistics & Data Analysis, Elsevier, vol. 40(2), pages 253-262, August.
    2. Hu Yang & Jianwen Xu, 2009. "An alternative stochastic restricted Liu estimator in linear regression," Statistical Papers, Springer, vol. 50(3), pages 639-647, June.
    3. Groß, Jürgen, 2003. "Restricted ridge estimation," Statistics & Probability Letters, Elsevier, vol. 65(1), pages 57-64, October.
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