Model robust extrapolation designs

DOI10.1016/0378-3758(88)90012-2zbMath0649.62069OpenAlexW2077333655MaRDI QIDQ1105959

Mong-Na Lo Huang, William J. Studden

Publication date: 1988

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0378-3758(88)90012-2

zbMATH Keywords

Chebyshev polynomialslinear estimationextrapolationrobust designsapproximate designminimax risk designsn point experimental design \(\xi \)

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Optimal statistical designs (62K05) Robustness and adaptive procedures (parametric inference) (62F35) Minimax procedures in statistical decision theory (62C20)

Related Items (8)

Admissible minimum bias estimation of response surfaces ⋮ Optimal extrapolation designs for a partly linear model ⋮ Extrapolation designs with constraints ⋮ Robust designs for probability estimation in binary response experiments ⋮ Optimal minimax designs over a prespecified interval in a heteroscedastic polynomial model ⋮ Robust designs for one-point extrapolation ⋮ Robust extrapolation designs for biased polynomial models ⋮ Robust extrapolation designs and weights for biased regression models with heteroscedastic errors

Cites Work

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• Some model robust designs in regression
• Robust regression designs when the design space consists of finitely many points
• Optimal designs for minimax extrapolation
• Robust designs for nearly linear regression
• Optimal robust designs: Linear regression in \(R^ k\).
• A practical guide to splines
• Optimal Designs on Tchebycheff Points
• Minimum Bias Estimation and Experimental Design for Response Surfaces
• A Basis for the Selection of a Response Surface Design

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