Statistical approaches to detection and quantification of a trend with return-on-investment application
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Author
Contributions
- Jacobs, Patricia A. - Contributor
- Naval Postgraduate School (U.S.). Dept. of Operations Research - Contributor
Publication
1992 - Available from National Technical Information Service, Monterey, Calif, California
Language
English
Word Count
13,750 words, Guess
Page Count
55 pages
Identifiers
- Open LibraryOL25505819M
- Internet Archivestatisticalapproa00gave
Alternate Titles
- NPS-OR-93-007.
Description
Mathematical models are formulated for the possible onset and growth in subsystem degradation. The model recognizes that the time of onset of a degrading trend may be random, and hence initially unknown, and that the trend magnitude is also initially unknown. The trend magnitude will become better known as more data are accumulated. Maximum likelihood and Bayesian statistical procedures to estimate the time of onset and the trend magnitude are presented. A cost model is formulated to develop procedures (which recognize the uncertainty concerning the time of onset and trend magnitude) to determine estimated costs and the associated risks of upgrading the subsystem at different times in the future. Results of simulation studies of the procedures are presented.... Changepoint problems, Maximum likelihood, Bayesian procedures, Cost of system upgrade.
Subjects
Topics
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