Parametric Bootstrapping Predictive Estimator for Logistic Regression

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Kunio Takezawa


This paper proposes a method for constructing a predictive estimator for logistic regression. We make a provisional assumption that the predictive estimator is given by multiplying the maximum likelihood estimators by constants, which are estimated using a parametric bootstrap method. The relative merits of the maximum likelihood estimator and the predictive estimator produced by this method are determined by cross-validation. The results show that the predictive
estimators derived by this method lead to a smaller deviance than that obtained by the maximum likelihood estimator in many instances.

Log-likelihood, future data, predictive estimator, logistic regression, maximum likelihood estimator, parametric bootstrap method.

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How to Cite
Takezawa, K. (2019). Parametric Bootstrapping Predictive Estimator for Logistic Regression. Journal of Advances in Mathematics and Computer Science, 32(5), 1-15.
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