Robustness of subset response surface designs to missing observations

Ahmad, Tanvir and Gilmour, Steven G. (2010) Robustness of subset response surface designs to missing observations. Journal of Statistical Planning and Inference, 140, (1), 92-103. (doi:10.1016/j.jspi.2009.06.011).


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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.

Item Type: Article
Digital Object Identifier (DOI): doi:10.1016/j.jspi.2009.06.011
ISSNs: 0378-3758 (print)
1873-1171 (electronic)
Keywords: response surface methodology, missing observations, subset design, minimax loss criterion, prediction variance
Subjects: H Social Sciences > HA Statistics
H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
Divisions : University Structure - Pre August 2011 > School of Mathematics > Statistics
ePrint ID: 174553
Accepted Date and Publication Date:
1 January 2010Published
Date Deposited: 14 Feb 2011 16:22
Last Modified: 31 Mar 2016 13:32

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