Model averaging for linear models with responses missing at random

Yuting Wei (), Qihua Wang () and Wei Liu ()
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Yuting Wei: University of Science and Technology of China
Qihua Wang: Zhejiang Gongshang University
Wei Liu: York University

Annals of the Institute of Statistical Mathematics, 2021, vol. 73, issue 3, No 5, 535-553

Abstract: 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.

Keywords: Missing responses; Missing at random; Model averaging; Asymptotic optimality (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s10463-020-00759-y

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