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Modelling multivariate data using product copulas and minimum distance estimators: an exemplary application to ecological traits
Environmental and Ecological Statistics ( IF 3.0 ) Pub Date : 2022-01-04 , DOI: 10.1007/s10651-021-00525-0
Eckhard Liebscher 1 , David Waltschew 1 , Franziska Taubert 2 , Jessica Hetzer 2
Affiliation  

Modelling and applying multivariate distributions is an important topic in ecology. In particular in plant ecology, the multidimensional nature of plant traits comes with challenges such as wide ranges in observations as well as correlations between several characteristics. In other disciplines (e.g., finances and economics), copulas have been proven as a valuable tool for modelling multivariate distributions. However, applications in ecology are still rarely used. Here, we present a copula-based methodology of fitting multivariate distributions to ecological data. We used product copula models to fit multidimensional plant traits, on example of observations from the global trait database TRY. The fitting procedure is split into two parts: fitting the marginal distributions and fitting the copula. We found that product copulas are well suited to model ecological data as they have the advantage of being asymmetric (similar to the observed data). Challenges in the fitting were mainly addressed to limited amount of data. In view of growing global databases, we conclude that copula modelling provides a great potential for ecological modelling.



中文翻译:

使用乘积 copula 和最小距离估计器对多元数据建模:生态特性的示例应用

建模和应用多元分布是生态学中的一个重要课题。特别是在植物生态学中,植物性状的多维性质带来了挑战,例如观察范围广泛以及几个特征之间的相关性。在其他学科(例如,金融和经济学)中,copula 已被证明是建模多元分布的重要工具。然而,在生态学中的应用仍然很少使用。在这里,我们提出了一种将多元分布拟合到生态数据的基于 copula 的方法。我们使用产品 copula 模型来拟合多维植物性状,例如来自全球性状数据库 TRY 的观察结果。拟合过程分为两部分:拟合边缘分布和拟合 copula。我们发现乘积 copula 非常适合对生态数据建模,因为它们具有不对称的优势(类似于观察到的数据)。拟合中的挑战主要针对有限的数据量。鉴于全球数据库不断增长,我们得出结论,copula 建模为生态建模提供了巨大的潜力。

更新日期:2022-01-05
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