To Survive or to Fail: That is the Question
作者:
PatriciaS. Abel,
NozerD. Singpurwalla,
期刊:
The American Statistician
(Taylor Available online 1994)
卷期:
Volume 48,
issue 1
页码: 18-21
ISSN:0003-1305
年代: 1994
DOI:10.1080/00031305.1994.10476012
出版商: Taylor & Francis Group
关键词: Accelerated testing;Censoring;Entropy;Exponential distribution;Fisher information;Life testing;Parameterization;Shannon information;Uncertainty
数据来源: Taylor
摘要:
A question that naturally arises in life testing is the following: “During the conduct of the test, what would you rather observe, a failure or a survival?” Most people answer this question by saying failure, because intuitively, failures are presumed to provide more information about the parameters of a failure model than survivals. The aim of this article is to point out that such intuition could be misleading and that the answer depends on the particular parameterization that is chosen. The argument is made through the use of Shannon's measure of information in an experiment, with the exponential as an example.
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