文章基本信息

标题：Sensitivity analysis of a hierarchical qualitative model – the analysis of MASC
本地全文：下载
作者：Marta Carpani ; Marta Carpani ; Jacques-Eric Bergez 等
期刊名称：Procedia - Social and Behavioral Sciences
印刷版ISSN：1877-0428
出版年度：2010
卷号：2
期号：6
页码：7627-7628
DOI：10.1016/j.sbspro.2010.05.150
语种：English
出版社：Elsevier
摘要：AbstractSensitivity Analysis (SA) is applied to a hierarchical qualitative model built to assess the sustainability of cropping systems. Three approaches were tested to perform a first-order SA on such a model, assuming a fixed model structure and no correlation among input variables: (i) factorial designs combined with analysis of variance (ANOVA), (ii) conditional probabilities, (iii) Monte Carlo sampling (MC). If the complete factorial design is too large to be computed, MC and conditional probabilities represent efficient alternatives to perform an analysis of the overall qualitative model. Conditional probabilities exploit the hierarchical structure of the model to give exact first-order indices, while MC could be a more flexible approach for the introduction of correlations among variables. We discuss how such SA results can guide modellers and end-users in modelling and application phases.
关键词：sensitivity index;ANOVA;Monte Carlo;conditional probabilities;hierarchical model;qualitative model;agricultural sustainability