How Pooling Failure Data May Reverse Increasing Failure Rates
作者:
John Gurland,
Jayaram Sethuraman,
期刊:
Journal of the American Statistical Association
(Taylor Available online 1995)
卷期:
Volume 90,
issue 432
页码: 1416-1423
ISSN:0162-1459
年代: 1995
DOI:10.1080/01621459.1995.10476647
出版商: Taylor & Francis Group
关键词: Failure rate;Mixtures;Pooling;Proportional hazards
数据来源: Taylor
摘要:
Although mixtures of decreasing failure rate (DFR) distributions are always DFR, some mixtures of increasing failure rate (IFR) distributions can also be ultimately DFR. In this article various types of discrete and continuous mixtures of IFR distributions are considered, and conditions are developed for such mixtures to be ultimately DFR. These conditions lead to an interesting result—that certain mixtures of IFR distributions, even those with very rapidly increasing failure rates (e.g., Weibull, truncated extreme), ultimately become DFR distributions. It is common practice to pool data from several different IFR distributions to enlarge sample size, for instance. The results of this article sound a warning that such pooling may actually reverse the IFR property of the individual samples to a DFR property.
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