Nonparametric estimation of aging intensity function for right-censored dependent data

Aging Intensity (AI) function is a quantitative measure of hazard function (hazard rate/failure rate), which is used for evaluating the aging behaviour of a component/system. Although variety of research are now available on various properties such as modelling and analysis of AI function; however, a detailed theoretical study on the estimation of the same has not been considered. Accordingly, in the present study, we propose two nonparametric estimators for aging intensity function based on right-censored dependent data scheme and study their properties. Asymptotic properties of the estimators are established under suitable regularity conditions. A simulation study and real data analysis have been carried out to illustrate the performance of the estimators.