Selection between Weibull and lognormal distributions: A comparative simulation study

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How to select the correct distribution for a given set of data is an important issue, especially when the tail probabilities are of interest as in lifetime data analysis. The Weibull and lognormal distributions are assumed most often in analyzing lifetime data, and in many cases, they are competing with each other. In addition, lifetime data are usually censored due to the constraint on the amount of testing time. A literature review reveals that little attention has been paid to the selection problems for the case of censored samples. In this article, relative performances of the two selection procedures, namely, the maximized likelihood and scale invariant procedures are compared for selecting between the Weibull and lognormal distributions for the cases of not only complete but also censored samples. Monte Carlo simulation experiments are conducted for various combinations of the censoring rate and sample size, and the performance of each procedure is evaluated in terms of the probability of correct selection (PCS) and average error rate. Then, previously unknown behaviors and relative performances of the two procedures are summarized. Computational results suggest that the maximized likelihood procedure can be generally recommended for censored as well as complete sample cases. (C) 2008 Elsevier B.V. All rights reserved.
Publisher
ELSEVIER SCIENCE BV
Issue Date
2008-12
Language
English
Article Type
Article
Keywords

GENERALIZED EXPONENTIAL-DISTRIBUTIONS; LOG-NORMAL DISTRIBUTION; MODEL SELECTION; CORRECT SELECTION; LIKELIHOOD RATIO; PROBABILITY; RELIABILITY; GAMMA; DISCRIMINATION; TIME

Citation

COMPUTATIONAL STATISTICS DATA ANALYSIS, v.53, no.2, pp.477 - 485

ISSN
0167-9473
DOI
10.1016/j.csda.2008.08.012
URI
http://hdl.handle.net/10203/90997
Appears in Collection
IE-Journal Papers(저널논문)
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