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Optimal Model Averaging Estimation for the Varying-Coefficient Partially Linear Models with Missing Responses

Author

Listed:
  • Jie Zeng

    (School of Mathematics and Statistics, Hefei Normal University, Hefei 230601, China)

  • Weihu Cheng

    (Faculty of Science, Beijing University of Technology, Beijing 100124, China)

  • Guozhi Hu

    (School of Mathematics and Statistics, Hefei Normal University, Hefei 230601, China)

Abstract

In this paper, we propose a model averaging estimation for the varying-coefficient partially linear models with missing responses. Within this context, we construct a HR C p weight choice criterion that exhibits asymptotic optimality under certain assumptions. Our model averaging procedure can simultaneously address the uncertainty on which covariates to include and the uncertainty on whether a covariate should enter the linear or nonlinear component of the model. The simulation results in comparison with some related strategies strongly favor our proposal. A real dataset is analyzed to illustrate the practical application as well.

Suggested Citation

  • Jie Zeng & Weihu Cheng & Guozhi Hu, 2023. "Optimal Model Averaging Estimation for the Varying-Coefficient Partially Linear Models with Missing Responses," Mathematics, MDPI, vol. 11(8), pages 1-21, April.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:8:p:1883-:d:1124592
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    References listed on IDEAS

    as
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