Association Journal of CSIAM
Supervised by Ministry of Education of PRC
Sponsored by Xi'an Jiaotong University
ISSN 1005-3085  CN 61-1269/O1

Chinese Journal of Engineering Mathematics ›› 2023, Vol. 40 ›› Issue (1): 97-109.doi: 10.3969/j.issn.1005-3085.2023.01.007

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Orthogonal Projection Based Estimation for Mixed Effects Models with Incomplete Observations

ZHAO Peixin1,2,   ZHANG Fan1,   ZHOU Xiaoshuang3   

  1. 1. School of Mathematics and Statistics, Chongqing Technology and Business University, Chongqing 400067;
    2. Chongqing Key Laboratory of Social Economy and Applied Statistics, Chongqing 400067;
    3. College of Mathematics and Big Data, Dezhou University, Dezhou 253023
  • Online:2023-02-15 Published:2023-04-11
  • Supported by:
    The National Social Science Foundation of China (18BTJ035); the Ministry of Edu-cation Humanities and Social Sciences Research Youth Foundation (19YJC910011); the Natural Science Foundation of Shandong Province (ZR2020MA021); the Natural Science Foundation of Chongqing (cstc2020jcyj-msxmX0006; cstc2021jcyj-msxmX0079).

Abstract:

Based on the QR decomposition technique, estimation method based on an orthogonal projection is proposed for a class of linear mixed effects models with incomplete observations. Under regularity conditions, the proposed estimator for fixed effects is proved to be asymptotically normal distributed, and then the confidence intervals for the fixed effects are constructed. The proposed estimator for fixed effects is not affected by the random effects, and then is more effective and robust compared with existing estimation methods. Some simulations and a real data application are also conducted for further illustrating the performances of the proposed method.

Key words: linear mixed effects model, orthogonality estimation, incomplete observations, random effects

CLC Number: