D-optimal designs for multi-response linear mixed models

Xin Liu, Rong-Xian Yue () and Weng Kee Wong
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Xin Liu: Donghua University
Rong-Xian Yue: Shanghai Normal University
Weng Kee Wong: University of California

Metrika: International Journal for Theoretical and Applied Statistics, 2019, vol. 82, issue 1, No 5, 87-98

Abstract: Abstract Linear mixed models have become popular in many statistical applications during recent years. However design issues for multi-response linear mixed models are rarely discussed. The main purpose of this paper is to investigate D-optimal designs for multi-response linear mixed models. We provide two equivalence theorems to characterize the optimal designs for the estimation of the fixed effects and the prediction of random effects, respectively. Two examples of the D-optimal designs for multi-response linear mixed models are given for illustration.

Keywords: D-optimal designs; Multi-response; Linear mixed model; Equivalence theorem (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (5)

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DOI: 10.1007/s00184-018-0679-7

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