On a Model for Bivariate Left Censored Data

TL;DR

This paper introduces a class of distributions based on proportional reversed hazard rates for analyzing left-censored data, providing new characterizations, simulation methods, and real data analysis techniques.

Contribution

It develops novel properties and characterizations of distributions using proportional reversed hazard rates specifically for left-censored data analysis.

Findings

New distribution class characterized by proportional reversed hazard rates

Simulation methods for the proposed distributions

Application to real left-censored data analysis

Abstract

The lifetimes of subjects which are left-censored lie below a threshold value or a limit of detection. A popular tool used to handle left-censored data is the reversed hazard rate. In this work, we study the properties and develop characterizations of a class of distributions based on proportional reversed hazard rates used for analyzing left censored data. These characterizations are applied to simulate samples as well as analyze real data using distributions belonging to this class.