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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...
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A common approach in the design of experiment for the problem of comparing two means from a normal distribution is to … to the design of experiment for bioassay is presented. …
Persistent link: https://www.econbiz.de/10010477495
The Monod model is a classical microbiological model much used in microbiology, for example to evaluate biodegradation processes. The model describes microbial growth kinetics in batch culture experiments using three parameters: the maximal specific growth rate, the saturation constant and the...
Persistent link: https://www.econbiz.de/10003355230
In this paper optimal experimental designs for inverse quadratic regression models are determined. We consider two dfferent parameterizations of the model and investigate local optimal designs with respect to the c-, D-and E-criteria, which reflect various aspects of the precision of the maximum...
Persistent link: https://www.econbiz.de/10003835646
In this paper robust and efficient designs are derived for several exponential decay models. These models are widely used in chemistry, pharmacokinetics or microbiology. We propose a maximin approach, which determines the optimal design such that a minimum of the D-efficiencies (taken over a...
Persistent link: https://www.econbiz.de/10010306252
We consider a class of optimality criteria and show that each crite- rion has its unique and equivalent dual within the class. This property can be used to find a variety of optimal designs, including a class of compound optimal designs and their relationships. As an example, we show that one...
Persistent link: https://www.econbiz.de/10010296610
can be decreased by a factor two by simply sampling at optimal times during the experiment. Moreover, the maximin optimal …
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