Estimation of the hazard rate function in the presence of measurement errors

In this article, according to the importance of the hazard rate function criterion in the evaluation of statistical distributions, its estimation methods are presented. Here, we suggest estimators for the hazard rate function. First, we use the standard deconvolution kernel density estimator and suggest a plug-in estimator. In the following we investigate asymptotic behavior of our estimator. For another estimator, we construct the new estimation the hazard rate function according plug-in and CDF. Finally, we consider the performance of the suggested estimators by simulation.