The generalized Pareto law as a model for progressively censored survival data

Abstract

The generalized Pareto distribution as a model for survival data is considered. The three parameter model is general enough so as to include increasing, decreasing and constant failure rate distributions. Maximum likelihood estimation for the progressively censored case is discussed at length and conditions for existence and uniqueness of estimates are given. Examples are presented to illustrate its appropriateness for a variety of situations.