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- W2890691412 abstract "Information Capacity (IC) is a criterion for selecting a design for an experiment based on its effectiveness in estimating a set of models to be investigated in the data analysis (Li and Nachtsheim (2000)). This presentation will describe how this criterion can be applied to experiments where a generalized linear model (GLM) describes the measured response. Three different types of IC designs will be compared with the aim of achieving accurate estimation of the models in the set and discriminating between the competing models. Recent work on experiments for both estimation and discrimination in nonlinear models, includes Waterhouse et al. (2009)." @default.
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- W2890691412 date "2010-09-14" @default.
- W2890691412 modified "2023-09-27" @default.
- W2890691412 title "Information capacity designs for generalized linear models" @default.
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