Economics at your fingertips  

Multiple predictor smoothing methods for sensitivity analysis: Example results

Curtis B. Storlie and Jon C. Helton

Reliability Engineering and System Safety, 2008, vol. 93, issue 1, 55-77

Abstract: The use of multiple predictor smoothing methods in sampling-based sensitivity analyses of complex models is investigated. Specifically, sensitivity analysis procedures based on smoothing methods employing the stepwise application of the following nonparametric regression techniques are described in the first part of this presentation: (i) locally weighted regression (LOESS), (ii) additive models, (iii) projection pursuit regression, and (iv) recursive partitioning regression. In this, the second and concluding part of the presentation, the indicated procedures are illustrated with both simple test problems and results from a performance assessment for a radioactive waste disposal facility (i.e., the Waste Isolation Pilot Plant). As shown by the example illustrations, the use of smoothing procedures based on nonparametric regression techniques can yield more informative sensitivity analysis results than can be obtained with more traditional sensitivity analysis procedures based on linear regression, rank regression or quadratic regression when nonlinear relationships between model inputs and model predictions are present.

Keywords: Additive models; Epistemic uncertainty; Locally weighted regression; Nonparametric regression; Projection pursuit regression; Recursive partitioning regression; Scatterplot smoothing; Sensitivity analysis; Stepwise selection; Uncertainty analysis (search for similar items in EconPapers)
Date: 2008
References: View references in EconPapers View complete reference list from CitEc
Citations View citations in EconPapers (22) Track citations by RSS feed

Downloads: (external link)
Full text for ScienceDirect subscribers only

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:

Access Statistics for this article

Reliability Engineering and System Safety is currently edited by Carlos Guedes Soares

More articles in Reliability Engineering and System Safety from Elsevier
Series data maintained by Dana Niculescu ().

Page updated 2017-12-02
Handle: RePEc:eee:reensy:v:93:y:2008:i:1:p:55-77