sensobol: An R Package to Compute Variance-Based Sensitivity Indices
sensobol: An R Package to Compute Variance-Based Sensitivity Indices
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DOI：
10.18637/jss.v102.i05
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发表时间：
2022-04-01
影响因子：
5.8
通讯作者：
Levin, Simon A.
中科院分区：
文献类型：
--
作者：
Puy, Arnald;Lo Piano, Samuele;Levin, Simon A.
R包sensobol提供了几个函数来进行基于方差的不确定性和敏感性分析，从敏感性指标的估计到结果的可视化表示。它实现了几个最先进的一阶和全阶估计器，并允许以一种快速和用户友好的方式计算高达四阶的效应，以及近似误差。它的灵活性使得它也适用于具有标量输出或多变量输出的模型。我们通过对三个经典模型进行基于方差的敏感性分析来说明其功能：（1998） G函数，Verhulst（1845）的logistic种群增长模型，Ludwig, Jones, and Holling（1976）的云杉budworm和森林模型。
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 Sob ol??? (1998) G function, the logistic population growth model of Verhulst (1845), and the spruce budworm and forest model of Ludwig, Jones, and Holling (1976).