Robustness of subset response surface designs to missing observations

Tanvir Ahmad; Steven G. Gilmour

doi:10.1016/j.jspi.2009.06.011

Robustness of subset response surface designs to missing observations

Tanvir Ahmad, Steven G. Gilmour^*

^*Corresponding author for this work

Queen Mary University of London

Research output: Contribution to journal › Article › peer-review

31 Citations (Scopus)

Abstract

Experiments designed to investigate the effect of several factors on a process have wide application in modern industrial and scientific research. Response surface designs allow the researcher to model the effects of the input variables on the response of the process. Missing observations can make the results of a response surface experiment quite misleading, especially in the case of one-off experiments or high cost experiments. Designs robust to missing observations can attract the user since they are comparatively more reliable. Subset designs are studied for their robustness to missing observations in different experimental regions. The robustness of subset designs is also improved for multiple levels by using the minimax loss criterion.

Original language	English
Pages (from-to)	92-103
Number of pages	12
Journal	JOURNAL OF STATISTICAL PLANNING AND INFERENCE
Volume	140
Issue number	1
DOIs	https://doi.org/10.1016/j.jspi.2009.06.011
Publication status	Published - 1 Jan 2010

Keywords

Minimax loss criterion
Missing observations
Prediction variance
Response surface methodology
Subset design

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10.1016/j.jspi.2009.06.011

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Robustness of subset response surface designs to missing observations

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Keywords

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