Premium
Conditional Lifetime Data Analysis Using the Limited Expected Value Function
Author(s) -
Quigley John,
Walls Lesley
Publication year - 2004
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.559
Subject(s) - censoring (clinical trials) , mean time between failures , computer science , statistics , econometrics , reliability engineering , mathematics , failure rate , engineering
Much failure, and other event, data are commonly highly censored. Consequently this limits the efficacy of many statistical analysis techniques. The limited expected value (LEV) function presents an alternative way of characterizing lifetime distributions. In essence the LEV provides a means of calculating a truncated mean time to failure (MTTF) (or mean time before failure (MTBF) if appropriate) that is adjusted at each of the censoring times and so appears potentially suitable for dealing with censored data structures. In theory, the LEV has been defined for many standard distributions, however its practical use is not well developed. This paper aims to extend the theory of LEV for typical censoring structures to develop procedures that will assist in model identification as well as parameter estimation. Applications to typical event data will be presented and the use of LEV in comparison with a selection of existing lifetime distributional analysis will be made based on some preliminary research. Copyright © 2004 John Wiley & Sons, Ltd.