In this article, the problem of constructing efficient discriminating designs in a Fourier regression model is …

We investigate optimal designs for discriminating between exponential regression models of different complexity, which …

In this paper optimal experimental designs for inverse quadratic regression models are determined. We consider two … regression models. In particular it is demonstrated that for a sufficiently large design space geometric allocation rules are … optimality criteria are studied, and the effiiency of some commonly used designs are investigated. -- rational regression models …

In the common Fourier regression model we investigate the optimal design problem for estimating pairs of the … trigonometric regression model and the order of the terms for which the pair of the coe±cients has to be estimated. -- L …-optimal designs ; Fourier regression models ; parameter subsets ; equivalence theorem …

that a given design is an all-bias design and illustrate these in the special case of spline regression models. In … particular our results generalize recent findings of Woods and Lewis (2006). -- all-bias design ; spline regression models …

In the common linear regression model we consider the problem of designing experiments for estimating the slope of the … expected response in a regression. We discuss locally optimal designs, where the experimenter is only interested in the slope … the regression functions form a Chebyshev system. For polynomial regression and Fourier regression models of arbitrary …

We consider the common nonlinear regression model where the variance as well as the mean is a parametric function of … corresponding to a heteroscedastic regression model is the convex hull of a set of ellipsoids induced by the underlying model and … including pharmacokinetic models with random effects. -- c-optimal design ; heteroscedastic regression ; Elfving's theorem …

A new test for strict monotonicity of the regression function is proposed which is based on a composition of an … estimate of the inverse of the regression function with a common regression estimate. This composition is equal to the identity … if and only if the "trueʺ regression function is strictly monotone, and a test based on an L 2-distance is investigated …