Response surface designs robust to missing observations

DOI10.1080/03610918608812512zbMath0606.62078OpenAlexW2022440059MaRDI QIDQ3745092

Munir Akhtar, Philip Prescott

Publication date: 1986

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918608812512

zbMATH Keywords

outliersD-optimalitymissing valuesresponse surface designrotatable designsrobustness criteriaCentral composite designsminimax loss-of-efficiency criterionoutlier-robust designs

Mathematics Subject Classification ID

Optimal statistical designs (62K05) Design of statistical experiments (62K99)

Related Items (13)

Multilevel Augmented Pairs Second-Order Response Surface Designs and Their Robustness to Missing Data ⋮ Robustness of classical and optimal designs to missing observations ⋮ Factorial and response surface designs robust to missing observations ⋮ Some new third order designs robust to one missing observation ⋮ Equi-information robust designs: Which designs are possible? ⋮ Effects of missing observations on predictive capability of augmented Box-Behnken designs ⋮ Robustness of orthogonal uniform composite designs against missing data ⋮ Robustness of definitive screening composite designs to missing observations ⋮ Robustness to missing observation and optimalities of response surface designs with regular and complex structure ⋮ Robustness of orthogonal-array based composite designs to missing data ⋮ Efficient response surface designs for the second-order multivariate polynomial model robust to missing observation ⋮ Robustness of subset response surface designs to missing observations ⋮ \(D\)-optimal orthogonal array minus \(t\) run designs

Cites Work

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• The robustness and optimality of response surface designs
• Multi-Factor Experimental Designs for Exploring Response Surfaces
• Optimum Designs in Regression Problems
• The Equivalence of Two Extremum Problems
• Effect of missing plots in some response surface designs
• Developments in the Design of Experiments, Correspondent Paper
• Robust designs
• Linear Statistical Inference and its Applications

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