A Study on Imputing Censored Observations for Exponential Distribution Based on Random Censoring

DOI

10.2991/jcis.2006.119How to use a DOI?

Keywords

Censoring time, Imputation value, exponential distribution

Abstract

Censoring models are frequently employed in reliability analysis to reduce experimental time. There are three censoring model: type-I, type-II and random censoring. In this study, we focus on the right-random censoring model. In the previous literature, an imputation of the censored observation is considered as the censoring time (Miller (1981), Lawless (1982), Lee (1992) and among others). Clearly, the censored observation is imputed by the censoring time to underestimate the original failure time. In this paper, we consider the failure time to follow an exponential distribution, and alternatively we attempt to propose three measures to impute the censored observations. By Monte Carlo simulation, the goodness of fit test is employed to compare the four methods of imputing censored observations. It is found that the method of imputing censored data by censoring time little outperforms the other three imputing methods.

Copyright

© 2006, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Kuo-Ching Chiou
PY  - 2006/10
DA  - 2006/10
TI  - A Study on Imputing Censored Observations for Exponential Distribution Based on Random Censoring
BT  - Proceedings of the 9th Joint International Conference on Information Sciences (JCIS-06)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/jcis.2006.119
DO  - 10.2991/jcis.2006.119
ID  - Chiou2006/10
ER  -