Zobrazeno 1 - 10
of 87
pro vyhledávání: '"NEŠLEHOVÁ, JOHANNA G."'
Weak convergence of maxima of dependent sequences of identically distributed continuous random variables is studied under normalizing sequences arising as subsequences of the normalizing sequences from an associated iid sequence. This general framewo
Externí odkaz:
http://arxiv.org/abs/2405.02833
When modeling multivariate phenomena, properly capturing the joint extremal behavior is often one of the many concerns. Archimax copulas appear as successful candidates in case of asymptotic dependence. In this paper, the class of Archimax copulas is
Externí odkaz:
http://arxiv.org/abs/2210.15622
Bayes spaces were initially designed to provide a geometric framework for the modeling and analysis of distributional data. It has recently come to light that this methodology can be exploited to provide an orthogonal decomposition of bivariate proba
Externí odkaz:
http://arxiv.org/abs/2206.13898
Publikováno v:
In Journal of Multivariate Analysis September 2024 203
Publikováno v:
Environmetrics 32.4 (2021): e2668
Analyses of environmental phenomena often are concerned with understanding unlikely events such as floods, heatwaves, droughts or high concentrations of pollutants. Yet the majority of the causal inference literature has focused on modelling means, r
Externí odkaz:
http://arxiv.org/abs/2109.03757
Methods are developed for checking and completing systems of bivariate and multivariate Kendall's tau concordance measures in applications where only partial information about dependencies between variables is available. The concept of a concordance
Externí odkaz:
http://arxiv.org/abs/2009.08130
Publikováno v:
In Journal of Multivariate Analysis November 2023 198
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Publikováno v:
In Journal of Multivariate Analysis September 2022 191
Publikováno v:
Journal of Multivariate Analysis 169 (2019) 400-422
Correlation matrices are omnipresent in multivariate data analysis. When the number d of variables is large, the sample estimates of correlation matrices are typically noisy and conceal underlying dependence patterns. We consider the case when the va
Externí odkaz:
http://arxiv.org/abs/1706.05940