EconPapers    
Economics at your fingertips  
 

Variance‐Based Importance Analysis Applied to a Complex Probabilistic Performance Assessment

Randall D. Manteufel

Risk Analysis, 1996, vol. 16, issue 4, 587-598

Abstract: The most important input parameters in a complex probabilistic performance assessment are identified using a variance‐based method and compared with those identified using a regression‐based method. The variance‐based method has the advantage of not requiring assumptions about the functional relationship between input and output parameters. However, it has the drawback of requiring heuristic assessments of threshold variance ratios above which a parameter is considered important, and it also requires numerous executions of the computer program, which may be computationally expensive. Both methods identified the same top 5 and 7 of the top 10 most important parameters for a system having 195 inputs. Although no distinct advantage for the variance‐based approach was identified, the ideas which motivate the new approach are sound and suggest new avenues for exploring the relationships between the inputs and the output of a complex system.

Date: 1996
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://doi.org/10.1111/j.1539-6924.1996.tb01104.x

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wly:riskan:v:16:y:1996:i:4:p:587-598

Access Statistics for this article

More articles in Risk Analysis from John Wiley & Sons
Bibliographic data for series maintained by Wiley Content Delivery ().

 
Page updated 2025-03-20
Handle: RePEc:wly:riskan:v:16:y:1996:i:4:p:587-598