Optimal Designs for Random Coefficient Regression Models with Heteroscedastic Errors

DOI10.1080/03610926.2011.620211zbMath1275.62055OpenAlexW2037128116MaRDI QIDQ2859317

Jing Cheng, Xin Liu, Rong-Xian Yue

Publication date: 7 November 2013

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2011.620211

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Optimal statistical designs (62K05)

Related Items (5)

\(DS\)-optimal designs for random coefficient first-degree regression model with heteroscedastic errors ⋮ D-optimal designs for linear mixed model with random effects of Dirichlet process ⋮ Optimal designs for panel data linear regressions ⋮ Optimal designs for heteroscedastic regression models with two parameters ⋮ \(D\)-optimal designs for hierarchical linear models with heteroscedastic errors

Cites Work

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• The linear minimax estimator of stochastic regression coefficients and parameters under quadrat\-ic loss function
• The optimality of single-group designs for certain mixed models
• Goodness of fit tests in random coefficient regression models
• Optimal designs in random coefficient cubic regression models
• Considerations on group-wise identical designs for linear mixed models
• \(V\)- and \(D\)-optimal population designs for the simple linear regression model with a random intercept term
• A Dirichlet random coefficient regression model for quality indicators

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