Statistical approaches to detection and quantification of a trend with return-on-investment application
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Authors
Gaver, Donald Paul
Jacobs, Patricia A.
Subjects
Changepoint problems, Maximum likelihood, Bayesian
procedures, Cost of system upgrade
Advisors
Date of Issue
1992-12
Date
1992-12
Publisher
Monterey, California. Naval Postgraduate School
Language
en_US
Abstract
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
Type
Technical Report
Description
Series/Report No
Department
Operations Research
Identifiers
NPS Report Number
NPS-OR-93-007
Sponsors
NAVAIR (AIR 419), Washington, D.C.
Funder
NAVAIR (AIR 419), Washington, D.C.
Format
Citation
Distribution Statement
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.