Optimal design for prediction in multiresponse linear models based on rectangular confidence region
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Publication:394101
DOI10.1016/j.jspi.2013.06.012zbMath1279.62154OpenAlexW1986344896MaRDI QIDQ394101
Rong-Xian Yue, Dennis K. J. Lin, Xin Liu
Publication date: 24 January 2014
Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jspi.2013.06.012
general equivalence theoremElfving's theoremmultiresponse linear modelsrectangular confidence regions
Related Items (4)
Elfving's theorem for \(R\)-optimality of experimental designs ⋮ D-optimal designs for multiresponse linear models with a qualitative factor ⋮ Optimal dose‐finding for efficacy–safety models ⋮ \(I_L\)-optimal designs for regression models under the second-order least squares estimator
Cites Work
- Optimal design of multi-response experiments using semi-definite programming
- Computing optimal designs of multiresponse experiments reduces to second-order cone program\-ming
- Elfving's theorem for \(D\)-optimality
- A new interpretation of optimality for \(E\)-optimal designs in linear regression models
- D-optimal designs for a multivariate regression model
- Some properties of multiresponse \(D\)-optimal designs
- A note on Bayesian \(c\)-and \(D\)-optimal designs in nonlinear regression models
- \(I^r_L\)-optimal designs for a hierarchically ordered system of regression models
- Optimality criteria for regression models based on predicted variance
- A Geometric Characterization of Optimal Designs for Regression Models with Correlated Observations
- Bayesian D-Optimal and Model Robust Designs in Linear Regression Models
- Elfving's Theorem and Optimal Designs for Quadratic Loss
- Design of experiments for parameter estimation in multiresponse situations
- Optimum Allocation in Linear Regression Theory
- Estimation and variable selection for semiparametric additive partial linear models
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