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In this article, the problem of constructing efficient discriminating designs in a Fourier regression model is considered. We propose designs which maximize the efficiency for the estimation of the coefficient corresponding to the highest frequency subject to the constraints that the...
Persistent link: https://www.econbiz.de/10003355140
We investigate optimal designs for discriminating between exponential regression models of different complexity, which are widely used in the biological sciences; see, e.g., Landaw (1995) or Gibaldi and Perrier (1982). We discuss different approaches for the construction of appropriate...
Persistent link: https://www.econbiz.de/10003358765
We consider the problem of finding D-optimal designs for estimating the coefficients in a weighted polynominal regression model with a certain efficiency function depending on two unknown parameters, which models he heteroscedastic error structure. This problem is tackled by adopting a Bayesian...
Persistent link: https://www.econbiz.de/10010476996
For the binary response model, we determine optimal designs which are robust wit respect to the misspecifications of the unknown parameters. We propose a maximin approach and provide a numerical method to identify the best two point designs for the commonly applied link functions. This method is...
Persistent link: https://www.econbiz.de/10010509827
In a recent paper Gonzalez Manteiga and Vilar Fernandez (1995) considered the problem of testing linearity of a regression under MA structure of the errors using a weighted L1-distance between a parametric and a nonparametric fit. They established asymptotic normality of the corresponding test...
Persistent link: https://www.econbiz.de/10009783008
For the problem of checking linearity in a heteroscedastic nonparametric regression model under a fixed design assumption we study maximin designs which maximize the minimum power of a nonparametric test over a broad class of alternatives from the assumed linear regression model. It is...
Persistent link: https://www.econbiz.de/10009783009
In the common nonparametric regression model y(i) = g(ti) + a (ti) ei , i=1….,n with i.i.d - noise and nonrepeatable design points ti we consider the problem of choosing an optimal design for the estimation of the regression function g. A minimax approach is adopted which searches for designs...
Persistent link: https://www.econbiz.de/10009783011
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