Model-robust designs in multiresponse situations
AbstractThe multiresponse model E(y[alpha]x)=[summation operator]l=1p[alpha] [theta][alpha]lf[alpha]l(x)+h[alpha](x), [alpha]=1,...,r, is considered, where h[alpha](x) is an unknown bias or contamination function from some class with a probability measure. Optimal designs are studied in terms of generalized least squares estimation and the average expected quadratic loss. The performance of the uniform design is also explored.
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Bibliographic InfoArticle provided by Elsevier in its journal Statistics & Probability Letters.
Volume (Year): 58 (2002)
Issue (Month): 4 (July)
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Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Krafft, Olaf & Schaefer, Martin, 1992. "D-Optimal designs for a multivariate regression model," Journal of Multivariate Analysis, Elsevier, vol. 42(1), pages 130-140, July.
- Yue, Rong-Xian, 2001. "A comparison of random and quasirandom points for nonparametric response surface design," Statistics & Probability Letters, Elsevier, Elsevier, vol. 53(2), pages 129-142, June.
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