Maximin designs for exponential growth models and heteroscedastic polynomial models
Imhof, Lorens A.
Ann. Statist., Tome 29 (2001) no. 2, p. 561-576 / Harvested from Project Euclid
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This paper is concerned with nonsequential optimal designs for a class of nonlinear growth models, which includes the asymptotic regression model. This design problem is intimately related to the problem of finding optimal designs for polynomial regression models with only partially known heteroscedastic structure. In each case, a straightforward application of the usual D­optimality criterion would lead to designs which depend on the unknown underlying parameters. To overcome this undesirable dependence a maximin approach is adopted. The theorem of Perron and Frobenius on primitive matrices plays a crucial role in the analysis.
Publié le : 2001-04-14
Classification:  Nonlinear design problem,  approximate design,  maximin criterion,  standardized criterion,  62K05 
@article{1009210553,
     author = {Imhof, Lorens A.},
     title = {Maximin designs for exponential growth models and
			 heteroscedastic polynomial models},
     journal = {Ann. Statist.},
     volume = {29},
     number = {2},
     year = {2001},
     pages = { 561-576},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1009210553}
}

Imhof, Lorens A. Maximin designs for exponential growth models and
			 heteroscedastic polynomial models. Ann. Statist., Tome 29 (2001) no. 2, pp.  561-576. http://gdmltest.u-ga.fr/item/1009210553/