文章基本信息

标题：sensobol: An R Package to Compute Variance-Based Sensitivity Indices
本地全文：下载
作者：Arnald Puy ; Samuele Lo Piano ; Andrea Saltelli 等
期刊名称：Journal of Statistical Software
印刷版ISSN：1548-7660
电子版ISSN：1548-7660
出版年度：2022
卷号：102
页码：1-37
DOI：10.18637/jss.v102.i05
语种：English
出版社：University of California, Los Angeles
摘要：The R package sensobol provides several functions to conduct variance-based uncertainty and sensitivity analysis, from the estimation of sensitivity indices to the visual representation of the results. It implements several state-of-the-art first and total-order estimators and allows the computation of up to fourth-order effects, as well as of the approximation error, in a swift and user-friendly way. Its flexibility makes it also appropriate for models with either a scalar or a multivariate output. We illustrate its functionality by conducting a variance-based sensitivity analysis of three classic models: the Sobol' (1998) G function, the logistic population growth model of Verhulst (1845), and the spruce budworm and forest model of Ludwig, Jones, and Holling (1976).