A graphical approach for evaluating and comparing designs for nonlinear models

André I. Khuri, Juneyoung Lee

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

A graphical approach is proposed for the purpose of assessing the overall prediction capability of a nonlinear design inside a region of interest R. A visual description is given of the behavior of the mean-squared error of prediction throughout the region R. More explicitly, for each of several concentric surfaces inside R, quantile plots of the so-called estimated scaled mean-squared error of prediction (ESMSEP) are obtained. In addition, when the number of control (input) variables in the associated model is equal to one, plots of the maximum and minimum of the scaled mean-squared error of prediction (SMSEP) over a subset of the model's parameter space are developed. The latter plots are primarily used to compare several nonlinear designs. Two examples are presented to demonstrate the usefulness of the proposed plots.

Original languageEnglish
Pages (from-to)433-443
Number of pages11
JournalComputational Statistics and Data Analysis
Volume27
Issue number4
Publication statusPublished - 1998 Jun 5
Externally publishedYes

Fingerprint

Nonlinear Model
Mean Squared Error
Prediction
Concentric
Region of Interest
Quantile
Set theory
Parameter Space
Subset
Graphics
Design
Model
Demonstrate

Keywords

  • Nonlinear designs
  • Prediction bias
  • Prediction capability
  • Quantile plots
  • Scaled mean-squared error of prediction

ASJC Scopus subject areas

  • Statistics and Probability
  • Computational Mathematics
  • Computational Theory and Mathematics
  • Applied Mathematics

Cite this

A graphical approach for evaluating and comparing designs for nonlinear models. / Khuri, André I.; Lee, Juneyoung.

In: Computational Statistics and Data Analysis, Vol. 27, No. 4, 05.06.1998, p. 433-443.

Research output: Contribution to journalArticle

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