Robust designs for multinomial models |
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Authors: | Ishapathik Das Siuli Mukhopadhyay |
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Institution: | 1. Department of Mathematics, Indian Institute of Technology Tirupati, Tirupati, India;2. ishapathik@iittp.ac.in;4. Department of Mathematics, Indian Institute of Technology Bombay, Mumbai, India |
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Abstract: | AbstractModel misspecification in generalized linear models (GLMs) occurs usually when the linear predictor and/or the link function assumed are incorrect. This article discusses the effect of such misspecification on design selection for multinomial GLMs and proposes the use of quantile dispersion graphs to select robust designs. Due to misspecification in the model, parameter estimates are usually biased and the designs are compared on the basis of their mean squared error of prediction. Several numerical examples including a real data set are presented to illustrate the proposed methodology. |
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Keywords: | Family of link functions Multivariate kriging Multivariate logistic link Quantile dispersion graphs |
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