AbstractWe establish an extension, to the case of multiple regression, of a result on minimax simple regression designs due to P. Huber. Designs are found which are minimax with respect to integrated mean squared error as the true response function varies over an L2-neighbourhood of (1) a p-dimensional plane or (2) a bivariate surface with possible interactions between the regressors
SIGLEAvailable from TIB Hannover: RR 8460(2000,43) / FIZ - Fachinformationszzentrum Karlsruhe / TIB ...
This thesis deals with two different yet related areas of optimal experimental design. In the first ...
[[abstract]]In this thesis, we are interested in finding optimal minimax designs for heteroscedastic...
We establish an extension, to the case of multiple regression, of a result on minimax simple regress...
AbstractWe establish an extension, to the case of multiple regression, of a result on minimax simple...
Abstract: We exhibit regression designs and weights which are robust against incorrectly specified r...
Designs for estimating the slope of a response surface are considered. Minimization of the variance ...
We consider robust methods for the construction of sampling designs in spatial studies. The designs ...
In the common nonparametric regression model y_i = g(t_i) + \sigma (t_i)\, \varepsilon_i,\,\, i = 1...
Background and objective: Binary response models are used in many real applications. For these m...
The design criterion considered is minimization of the variance of the estimated slope of a response...
Maximum variance (MV) and Standarized maximum variance (SMV) optimum designs for binary response mod...
To aid in the discrimination between two, possibly nonlinear, regression models, we study the constr...
We investigate the problem of designing for linear regression models, when the assumed model form is...
In this paper, we consider the problem of estimating the regression parameters in a multiple linear ...
SIGLEAvailable from TIB Hannover: RR 8460(2000,43) / FIZ - Fachinformationszzentrum Karlsruhe / TIB ...
This thesis deals with two different yet related areas of optimal experimental design. In the first ...
[[abstract]]In this thesis, we are interested in finding optimal minimax designs for heteroscedastic...
We establish an extension, to the case of multiple regression, of a result on minimax simple regress...
AbstractWe establish an extension, to the case of multiple regression, of a result on minimax simple...
Abstract: We exhibit regression designs and weights which are robust against incorrectly specified r...
Designs for estimating the slope of a response surface are considered. Minimization of the variance ...
We consider robust methods for the construction of sampling designs in spatial studies. The designs ...
In the common nonparametric regression model y_i = g(t_i) + \sigma (t_i)\, \varepsilon_i,\,\, i = 1...
Background and objective: Binary response models are used in many real applications. For these m...
The design criterion considered is minimization of the variance of the estimated slope of a response...
Maximum variance (MV) and Standarized maximum variance (SMV) optimum designs for binary response mod...
To aid in the discrimination between two, possibly nonlinear, regression models, we study the constr...
We investigate the problem of designing for linear regression models, when the assumed model form is...
In this paper, we consider the problem of estimating the regression parameters in a multiple linear ...
SIGLEAvailable from TIB Hannover: RR 8460(2000,43) / FIZ - Fachinformationszzentrum Karlsruhe / TIB ...
This thesis deals with two different yet related areas of optimal experimental design. In the first ...
[[abstract]]In this thesis, we are interested in finding optimal minimax designs for heteroscedastic...
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