Optimal designs for generalized linear mixed models based on the penalized quasi-likelihood method

Yao Shi; Wanchunzi Yu; John Stufken

doi:10.1007/s11222-023-10279-3

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Optimal designs for generalized linear mixed models based on the penalized quasi-likelihood method

Yao Shi Wanchunzi Yu John Stufken

Year: 2023 Journal: Statistics and Computing Vol: 33 (5) Publisher: Springer Science+Business Media

DOI: 10.1007/s11222-023-10279-3

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Keywords:

Mathematics Mathematical optimization Optimal design Generalized linear mixed model Generalized linear model Robustness (evolution) Mixed model Random effects model Covariance matrix Covariance Linear model Algorithm Computer science Applied mathematics Statistics

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Optimal Experimental Design Methods

Social Sciences → Decision Sciences → Management Science and Operations Research

Advanced Multi-Objective Optimization Algorithms

Physical Sciences → Computer Science → Computational Theory and Mathematics

Probabilistic and Robust Engineering Design

Social Sciences → Decision Sciences → Statistics, Probability and Uncertainty

Optimal designs for generalized linear mixed models based on the penalized quasi-likelihood method

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