Optimal designs for heteroscedastic regression models with two parameters

DOI10.1080/02331888.2019.1702041zbMath1436.62379OpenAlexW2996393305MaRDI QIDQ5222208

M. Wilk, Alexander Yu. Zeigraev

Publication date: 1 April 2020

Published in: Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331888.2019.1702041

zbMATH Keywords

optimal designheteroscedastic errorsFCR modelRCR modelcriterion of optimality

Mathematics Subject Classification ID

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

Related Items (1)

D-optimal designs for linear mixed model with random effects of Dirichlet process

Cites Work

• Optimal design for linear regression models in the presence of heteroscedasticity caused by random coefficients
• Shape optimal design criterion in linear models
• Integral stochastic optimal design criteria in linear models
• On the de la Garza phenomenon
• Support points of locally optimal designs for nonlinear models with two parameters
• Optimal minimax designs for prediction in heteroscedastic models
• Computing optimal experimental designs with respect to a compound Bayes risk criterion
• R-optimal designs for multi-factor models with heteroscedastic errors
• \(DS\)-optimal designs for random coefficient first-degree regression model with heteroscedastic errors
• Optimal Designs for Random Coefficient Regression Models with Heteroscedastic Errors
• Optimal Designs for the Prediction of Individual Parameters in Hierarchical Models
• Spacing of Information in Polynomial Regression
• Topics in optimal design
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