Title :
The trunsored model and its applications to lifetime analysis: unified censored and truncated models
Author_Institution :
Dept. of Syst. Innovation & Informatics, Kyushu Inst. of Technol., Fukuoka, Japan
fDate :
3/1/2005 12:00:00 AM
Abstract :
A new incomplete data model, the trunsored model, in lifetime analysis is introduced. This model can be regarded as a unified model of the censored and truncated models. Using the model, we can not only estimate the ratio of the fragile population to the mixed fragile and durable populations, but also test a hypothesis that the ratio is equal to a prescribed value. A central point of the paper is that such a test can easily be realized through the newly introduced trunsored model, because it has been difficult to do such a hypothesis test under only the framework of censored and truncated models. Therefore, the relationship of the trunsored model to the censored and truncated models is clarified because the trunsored model unifies the censored and truncated models. The paper also shows how to obtain the estimates of the parameters in lifetime estimation, and corresponding confidence intervals for the fragile population. Typical examples applied to electronic board failures, and to breast cancer data, for lifetime estimation are demonstrated, and successfully worked using the trunsored model.
Keywords :
Weibull distribution; exponential distribution; failure analysis; life testing; maximum likelihood estimation; Weibull distribution; bootstrap; breast cancer data; censored data models; durable population; electronic board failures; exponential distribution; fragile population; incomplete data model; lifetime estimation analysis; likelihood ratio test; limited failure population; mixture model; truncated data; trunsored model; unified censor; Breast cancer; Data models; Exponential distribution; Life estimation; Lifetime estimation; Maximum likelihood estimation; Medical treatment; Parameter estimation; Testing; Weibull distribution; Bootstrap; Weibull distribution; censored data; durable population; exponential distribution; fragile population; grouped data; likelihood ratio test; limited failure population; mixture model; truncated data;
Journal_Title :
Reliability, IEEE Transactions on
DOI :
10.1109/TR.2004.837521