NSVineCopula: R package for modeling non-stationary multivariate dependence

IF 4.8 2区 环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Q. Zhang , Y.P. Li , G.H. Huang , X.M. Huang , H. Wang , Z. Wang , Z.P. Xu , Y.Y. Wang , Z.Y. Shen
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引用次数: 0

Abstract

A vine copula is a flexible method for multivariate dependence simulations that assumes stationarity. However, only a few studies have focused on non-stationarity and comprehensively developed nonstationary vine copula functions. In this study, a novel R package, NSVineCopula was developed and presented. Canonical-vine and Drawable-vine structure with 36 bivariate copula functions were considered in NSVineCopula. This package is capable of capturing non-stationary multivariate dependence, providing time-varying parameters for each bivariate copula, and quantifying the conditional probability. Notably, NSVineCopula provides a simple way for sampling non-stationary vine copulas. The capability of NSVineCopula was evaluated through two case studies: (1) agricultural drought risk assessment under compound dry-hot extreme conditions and water level prediction. The results demonstrate the advantages of NSVineCopula in non-stationary multivariate dependence analysis, and highlights the potential of NSVineCopula in many fields. Overall, NSVineCopula can provide valuable and robust functionalities for modeling nonstationary multivariate dependence.
NSVineCopula:非平稳多变量相关性建模的R包
vine copula是一种灵活的多变量相关性模拟方法。然而,只有少数研究关注非平稳,并全面发展了非平稳的藤联函数。在这项研究中,一个新的R包,NSVineCopula开发并提出。在NSVineCopula中考虑了具有36个二元联结函数的正则-藤和可拉-藤结构。该包能够捕获非平稳的多变量依赖,为每个二元联结提供时变参数,并量化条件概率。值得注意的是,NSVineCopula提供了一种简单的方法来采样非平稳的藤丛。通过两个案例对NSVineCopula的能力进行了评价:(1)复合干热极端条件下的农业干旱风险评估和水位预测。结果表明了NSVineCopula在非平稳多变量依赖分析中的优势,并突出了NSVineCopula在许多领域的潜力。总体而言,NSVineCopula可以为非平稳多变量依赖的建模提供有价值的鲁棒功能。
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来源期刊
Environmental Modelling & Software
Environmental Modelling & Software 工程技术-工程:环境
CiteScore
9.30
自引率
8.20%
发文量
241
审稿时长
60 days
期刊介绍: Environmental Modelling & Software publishes contributions, in the form of research articles, reviews and short communications, on recent advances in environmental modelling and/or software. The aim is to improve our capacity to represent, understand, predict or manage the behaviour of environmental systems at all practical scales, and to communicate those improvements to a wide scientific and professional audience.
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