D-optimal minimax regression designs on discrete design space

DOI10.1016/j.jspi.2008.03.013zbMath1146.62059OpenAlexW1974521626MaRDI QIDQ951076

Julie Zhou

Publication date: 29 October 2008

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.2008.03.013

zbMATH Keywords

symmetrysimulated annealingrobust designfinite design space

Mathematics Subject Classification ID

Optimal statistical designs (62K05) Applications of statistics to environmental and related topics (62P12) Response surface designs (62K20) Robust parameter designs (62K25)

Related Items (8)

Robust multistratum baseline designs ⋮ Minimax designs for linear regression models with bias in a reproducing kernel Hilbert space in a discrete set ⋮ On ExactK-optimal Designs Minimizing the Condition Number ⋮ D-optimal minimax design criterion for two-level fractional factorial designs ⋮ Application of imperialist competitive algorithm to find minimax and standardized maximin optimal designs ⋮ D-optimal minimax fractional factorial designs ⋮ K-Optimal Design via Semidefinite Programming and Entropy Optimization ⋮ Computing A-optimal and E-optimal designs for regression models via semidefinite programming

Cites Work

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• Optimal designs which are efficient for lack of fit tests
• Discrete minimax designs for regression models with autocorrelated MA errors
• Efficient \(D_ s\)-optimal designs for multivariate polynomial regression on the q-cube
• Optimal designs for regression models with possible bias
• Robust designs for nearly linear regression
• Minimax designs for approximately linear regression
• Robust designs for multivariate polynomial regression on the \(d\)-cube
• Optimal discrimination designs for multifactor experiments
• Robust designs for polynomial regression by maximizing a minimum of \(D\)- and \(D_1\)-efficiencies
• An algorithm for calculating \(\Gamma\)-minimax decision rules under generalized moment conditions.
• Existence and symmetry of minimax regression designs
• Lack-of-fit-efficiently optimal designs to estimate the highest coefficient of a polynomial with large degree
• Efficient lack of fit designs that are optimal to estimate the highest coefficient of a polynomial
• Matrix Analysis
• The Application of the Annealing Algorithm to the Construction of Exact Optimal Designs for Linear-Regression Models
• A two-stage strategy for the construction of d-optimal experimental designs
• An efficient design for model discrimination and parameter estimation in linear models
• Minimax designs for approximately linear models with AR(1) errors
• Minimax Robust Designs and Weights for Approximately Specified Regression Models with Heteroscedastic Errors
• Integer-Valued, Minimax Robust Designs for Estimation and Extrapolation in Heteroscedastic, Approximately Linear Models
• INTEGER-VALUED, MINIMAX ROBUST DESIGNS FOR APPROXIMATELY LINEAR MODELS WITH CORRELATED ERRORS
• Robustness properties of minimally-supported Bayesian D-optimal designs for heteroscedastic models
• Bayesian D-Optimal and Model Robust Designs in Linear Regression Models
• for misspecified regression models
• Experimental Designs for Model Discrimination
• A Basis for the Selection of a Response Surface Design
• Applications of necessary and sufficient conditions for maximin efficient designs

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