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Smoothed bootstrap bandwidth selection for nonparametric hazard rate estimation
Authors:Inés Barbeito  Ricardo Cao
Affiliation:Faculty of Computer Science, Department of Mathematics, Research Group MODES, CITIC, Universidade da Coru?a, A Coru?a, Spain
Abstract:A smoothed bootstrap method is presented for the purpose of bandwidth selection in nonparametric hazard rate estimation for iid data. In this context, two new bootstrap bandwidth selectors are established based on the exact expression of the bootstrap version of the mean integrated squared error of some approximations of the kernel hazard rate estimator. This is very useful since Monte Carlo approximation is no longer needed for the implementation of the two bootstrap selectors. A simulation study is carried out in order to show the empirical performance of the new bootstrap bandwidths and to compare them with other existing selectors. The methods are illustrated by applying them to a diabetes data set.
Keywords:Kernel method  hazard rate  mean integrated squared error  smoothing parameter  smooth bootstrap
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