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Model averaging for linear models with responses missing at random

Author

Listed:
  • Yuting Wei

    (University of Science and Technology of China)

  • Qihua Wang

    (Zhejiang Gongshang University
    Chinese Academy of Sciences)

  • Wei Liu

    (York University)

Abstract

In this paper, a model averaging approach is developed for the linear regression models with response missing at random. It is shown that the proposed method is asymptotically optimal in the sense of achieving the lowest possible squared error. A Monte Carlo study is conducted to investigate the finite sample performance of our proposal by comparing with some related methods, and the simulation results favor the proposed method. Moreover, a real data analysis is given to illustrate the practical application of our proposal.

Suggested Citation

  • Yuting Wei & Qihua Wang & Wei Liu, 2021. "Model averaging for linear models with responses missing at random," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(3), pages 535-553, June.
    • Handle: RePEc:spr:aistmt:v:73:y:2021:i:3:d:10.1007_s10463-020-00759-y
    DOI: 10.1007/s10463-020-00759-y
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    References listed on IDEAS

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