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Robustness of subset response surface designs to missing observations

Record type: Article

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.

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Citation

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

More information

Published date: 1 January 2010
Keywords: response surface methodology, missing observations, subset design, minimax loss criterion, prediction variance
Organisations: Statistics

Identifiers

Local EPrints ID: 174553
URI: http://eprints.soton.ac.uk/id/eprint/174553
ISSN: 0378-3758
PURE UUID: c72e929a-2763-4d75-881c-1628835f0659

Catalogue record

Date deposited: 14 Feb 2011 16:22
Last modified: 18 Jul 2017 12:11

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Contributors

Author: Tanvir Ahmad
Author: Steven G. Gilmour

University divisions

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