A graphical approach for evaluating and comparing designs for nonlinear models.

DOI10.1016/S0167-9473(98)00016-4zbMath1042.62501OpenAlexW2009544437MaRDI QIDQ1128897

Juneyoung Lee, André I. Khuri

Publication date: 13 August 1998

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0167-9473(98)00016-4

zbMATH Keywords

Nonlinear designsPrediction biasPrediction capabilityQuantile plotsScaled mean-squared error of prediction

Mathematics Subject Classification ID

Graphical methods in statistics (62A09)

Related Items (5)

Quantile dispersion graphs to compare the efficiencies of cluster randomized designs ⋮ Comparison of three-level cluster randomized trials using quantile dispersion graphs ⋮ Quantile dispersion graphs for evaluating and comparing designs for logistic regression models ⋮ Fraction of design space plots for generalized linear models ⋮ Discussion of ``Response surface design evaluation and comparison by Christine M. Anderson-Cook, Connie M. Borror, Douglas C. Montgomery

Cites Work

• Quantile plots of the prediction variance for response surface designs
• DESIGN OF EXPERIMENTS IN NON-LINEAR SITUATIONS
• A Quadratic Design Criterion for Precise Estimation in Nonlinear Regression Models
• Bias in nonlinear regression
• Recent Advances in Nonlinear Experimental Design
• Optimal design for nonlinear regression models
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