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Bootstrap and Asymptotic Prediction Criterion Estimates for Binomial Proportions in Insemination Data
Authors:M. Bonneu  C. Lavergne
Abstract:Model choice techniques are proposed for logistic regression, based on prediction criterion estimation similar to Akaike's information criterion. For artificial insemination data of cattle, we wish to study a factor influence on success proportion; tests standard methods don't always seem suitable for prediction objective. Two prediction criterion estimate methods are applied to these data: simulated bootstrap and asymptotic estimates. Some empirical properties of this estimate are studied.
Keywords:Generalized linear model  Model choice  Prediction criterion  Quantal response
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