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Ridge-type pretest and shrinkage estimations in partially linear models

Author

Listed:
  • Bahadır Yüzbaşı

    (Inonu University)

  • S. Ejaz Ahmed

    (Brock University)

  • Dursun Aydın

    (Mugla Sitki Kocman University)

Abstract

In this paper, we suggest pretest and shrinkage ridge regression estimators for a partially linear regression model, and compare their performance with some penalty estimators. We investigate the asymptotic properties of proposed estimators. We also consider a Monte Carlo simulation comparison, and a real data example is presented to illustrate the usefulness of the suggested methods.

Suggested Citation

  • Bahadır Yüzbaşı & S. Ejaz Ahmed & Dursun Aydın, 2020. "Ridge-type pretest and shrinkage estimations in partially linear models," Statistical Papers, Springer, vol. 61(2), pages 869-898, April.
    • Handle: RePEc:spr:stpapr:v:61:y:2020:i:2:d:10.1007_s00362-017-0967-8
    DOI: 10.1007/s00362-017-0967-8
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    References listed on IDEAS

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    1. M. Arashi & T. Valizadeh, 2015. "Performance of Kibria’s methods in partial linear ridge regression model," Statistical Papers, Springer, vol. 56(1), pages 231-246, February.
    2. Raheem, S.M. Enayetur & Ahmed, S. Ejaz & Doksum, Kjell A., 2012. "Absolute penalty and shrinkage estimation in partially linear models," Computational Statistics & Data Analysis, Elsevier, vol. 56(4), pages 874-891.
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    5. Roozbeh, Mahdi, 2015. "Shrinkage ridge estimators in semiparametric regression models," Journal of Multivariate Analysis, Elsevier, vol. 136(C), pages 56-74.
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    7. Eubank, R. L. & Kambour, E. L. & Kim, J. T. & Klipple, K. & Reese, C. S. & Schimek, M., 1998. "Estimation in partially linear models," Computational Statistics & Data Analysis, Elsevier, vol. 29(1), pages 27-34, November.
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    Full references (including those not matched with items on IDEAS)

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