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The weighted ridge estimator in stochastic restricted linear measurement error models

Author

Listed:
  • F. Ghapani

    (Shoushtar Branch, Islamic Azad University)

  • A. R. Rasekh

    (Shahid Chamran University of Ahvaz)

  • B. Babadi

    (Shahid Chamran University of Ahvaz)

Abstract

In this paper, we introduce the mixed ridge estimator (MRE) in linear measurement error models with stochastic linear restrictions and present the method of weighted mixed ridge estimation, which permits to assign possibly unequal weights to the prior information in relation to the sample information. The performance of the weighted mixed ridge estimator (WMRE) against the weighted mixed estimator (WME) is examined in terms of the mean squared error matrix (MSEM) of estimators. Finally, a simulation study and a numerical example are also given to show the theoretical results.

Suggested Citation

  • F. Ghapani & A. R. Rasekh & B. Babadi, 2018. "The weighted ridge estimator in stochastic restricted linear measurement error models," Statistical Papers, Springer, vol. 59(2), pages 709-723, June.
    • Handle: RePEc:spr:stpapr:v:59:y:2018:i:2:d:10.1007_s00362-016-0786-3
    DOI: 10.1007/s00362-016-0786-3
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    References listed on IDEAS

    as
    1. Özkale, M. Revan, 2009. "A stochastic restricted ridge regression estimator," Journal of Multivariate Analysis, Elsevier, vol. 100(8), pages 1706-1716, September.
    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. Rasekh, A.R., 2006. "Local influence in measurement error models with ridge estimate," Computational Statistics & Data Analysis, Elsevier, vol. 50(10), pages 2822-2834, June.
    Full references (including those not matched with items on IDEAS)

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