Efficient experimental designs for sigmoidal growth models - Holger Dette; Andrey Pepelyshev (Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen, 2005)
For the Weibull- and Richards-regression model robust designs are determined by maximizing a minimum of D- or D1-efficiencies, taken over a certain range of the non-linear parameters. It is demonstrated that the derived designs yield a satisfactory solution of the optimal design problem for this type of model in the sense that these designs are efficient and robust with respect to misspecification of the unknown parameters. Moreover, the designs can also be used for testing the postulated form of the regression model against a simplified sub-model.
Keywords: 519; Sigmoidal growth; Weibull regression model; exponential regression model; Richards-regression model; logistic regression model; Regression; Experiment; Theorie