Bootstrap bandwidth selection in kernel hazard rate estimation

Abstract

The purpose of this study is to thoroughly discuss kernel hazard function estimation, both in the complete sample case as well as in the presence of random right censoring. Most of the focus is on the very important task of automatic bandwidth selection. Two existing selectors, least-squares cross validation as described by Patil (1993a) and Patil (1993b), as well as the bootstrap bandwidth selector of Gonzalez-Manteiga, Cao and Marron (1996) will be discussed. The bandwidth selector of Hall and Robinson (2009), which uses bootstrap aggregation (or 'bagging'), will be extended to and evaluated in the setting of kernel hazard rate estimation. We will also make a simple proposal for a bootstrap bandwidth selector. The performance of these bandwidth selectors will be compared empirically in a simulation study. The findings and conclusions of this study are reported.