Evaluating prediction uncertainty

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Description

The probability distribution of a model prediction is presented as a proper basis for evaluating the uncertainty in a model prediction that arises from uncertainty in input values. Determination of important model inputs and subsets of inputs is made through comparison of the prediction distribution with conditional prediction probability distributions. Replicated Latin hypercube sampling and variance ratios are used in estimation of the distributions and in construction of importance indicators. The assumption of a linear relation between model output and inputs is not necessary for the indicators to be effective. A sequential methodology which includes an independent validation step is ... continued below

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66 p.

Creation Information

McKay, M.D. March 1, 1995.

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  • McKay, M.D. Los Alamos National Lab., NM (United States)

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Description

The probability distribution of a model prediction is presented as a proper basis for evaluating the uncertainty in a model prediction that arises from uncertainty in input values. Determination of important model inputs and subsets of inputs is made through comparison of the prediction distribution with conditional prediction probability distributions. Replicated Latin hypercube sampling and variance ratios are used in estimation of the distributions and in construction of importance indicators. The assumption of a linear relation between model output and inputs is not necessary for the indicators to be effective. A sequential methodology which includes an independent validation step is applied in two analysis applications to select subsets of input variables which are the dominant causes of uncertainty in the model predictions. Comparison with results from methods which assume linearity shows how those methods may fail. Finally, suggestions for treating structural uncertainty for submodels are presented.

Physical Description

66 p.

Notes

INIS; OSTI as TI95008324

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  • Other Information: PBD: Mar 1995

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  • Other: TI95008324
  • Report No.: NUREG/CR--6311
  • Report No.: LA--12915-MS
  • DOI: 10.2172/29432 | External Link
  • Office of Scientific & Technical Information Report Number: 29432
  • Archival Resource Key: ark:/67531/metadc680637

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Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

Office of Scientific and Technical Information (OSTI) is the Department of Energy (DOE) office that collects, preserves, and disseminates DOE-sponsored research and development (R&D) results that are the outcomes of R&D projects or other funded activities at DOE labs and facilities nationwide and grantees at universities and other institutions.

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Creation Date

  • March 1, 1995

Added to The UNT Digital Library

  • July 25, 2015, 2:20 a.m.

Description Last Updated

  • April 22, 2016, 6:42 p.m.

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McKay, M.D. Evaluating prediction uncertainty, report, March 1, 1995; Washington D.C.. (digital.library.unt.edu/ark:/67531/metadc680637/: accessed October 19, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.