Sensitivity analysis when model outputs are functions

被引：110

作者：

Campbell, Katherine ^{[1
]}

Mckay, Michael D. ^{[1
]}

Williams, Brian J. ^{[1
]}

机构：

[1] Los Alamos Natl Lab, Stat Sci Grp, Los Alamos, NM 87545 USA

来源：

RELIABILITY ENGINEERING & SYSTEM SAFETY | 2006年 / 91卷 / 10-11期

关键词：

functional sensitivity analysis; functional data analysis; basis functions;

D O I：

10.1016/j.ress.2005.11.049

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

When outputs of computational models are time series or functions of other continuous variables like distance, angle, etc., it can be that primary interest is in the general pattern or structure of the curve. In these cases, model sensitivity and uncertainty analysis focuses on the effect of model input choices and uncertainties in the overall shapes of such curves. We explore methods for characterizing a set of functions generated by a series of model runs for the purpose of exploring relationships between these functions and the model inputs. (c) 2005 Elsevier Ltd. All rights reserved.

引用

页码：1468 / 1472

页数：5