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Model checking for generalized partially linear models

Author

Listed:
  • Xinmin Li

    (Qingdao University)

  • Haozhe Liang

    (University of Science and Technology of China)

  • Wolfgang Härdle

    (Blockchain Research Center
    Xiamen University - Wang Yanan Institute for Studies in Economics (WISE)
    Charles University
    National Yang Ming Chiao Tung University)

  • Hua Liang

    (George Washington University)

Abstract

We propose a residual-marked empirical process test to check goodness of fit for generalized partially linear models. The proposed test can gain dimension reduction, is shown to be consistent, and can detect root-n local alternatives. We further establish asymptotic distributions of the proposed test under the null hypothesis and analyze asymptotic properties under the local and global alternatives, and suggest a bootstrap procedure for calculating the critical value. We investigate its numerical performance by simulation experiments and illustrate its utilization in two real data examples.

Suggested Citation

  • Xinmin Li & Haozhe Liang & Wolfgang Härdle & Hua Liang, 2024. "Model checking for generalized partially linear models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 33(2), pages 361-378, June.
    • Handle: RePEc:spr:testjl:v:33:y:2024:i:2:d:10.1007_s11749-023-00897-4
    DOI: 10.1007/s11749-023-00897-4
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    References listed on IDEAS

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    1. He, Xuming & Fung, Wing K. & Zhu, Zhongyi, 2005. "Robust Estimation in Generalized Partial Linear Models for Clustered Data," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 1176-1184, December.
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    6. Escanciano, J. Carlos, 2006. "A Consistent Diagnostic Test For Regression Models Using Projections," Econometric Theory, Cambridge University Press, vol. 22(6), pages 1030-1051, December.
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