Statistical approaches to detection and quantification of a trend with return-on-investment application
By: Donald P. Gaver, Patricia A. Jacobs
Contributors: Jacobs, Patricia A.; Naval Postgraduate School (U.S.). Dept. of Operations Research
Publisher: Naval Postgraduate School; Available from National Technical Information Service
Published: 1992
Place of publication: Monterey, Calif; Springfield, Va
Language: eng
Number of pages: 55
Subjects: SYSTEMS ANALYSIS; MATHEMATICAL MODELS; COST MODELS
Other 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.
Notes: Title from cover.

"NPS-OR-93-007."

"December 1992."

AD A260 188.

Includes bibliographical references (p. 13).

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