文章基本信息

标题：Smooth bootstrapping of copula functionals
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作者：Maximilian Coblenz ; Oliver Grothe ; Klaus Herrmann 等
期刊名称：Electronic Journal of Statistics
印刷版ISSN：1935-7524
出版年度：2022
卷号：16
期号：1
页码：2550-2606
DOI：10.1214/22-EJS2007
语种：English
出版社：Institute of Mathematical Statistics
摘要：The smooth bootstrap for estimating copula functionals in small samples is investigated. It can be used both to gauge the distribution of the estimator in question and to augment the data. Issues arising from kernel density and distribution estimation in the copula domain are addressed, such as how to avoid the bounded domain, which bandwidth matrix to choose, and how the smoothing can be carried out. Furthermore, we investigate how the smooth bootstrap impacts the underlying dependence structure or the functionals in question and under which conditions it does not. We provide specific examples and simulations that highlight advantages and caveats of the approach.
关键词：Bandwidth matrix;Bandwidth selection;Data augmentation;dependence distortion;Kernel distribution estimation;kernel smoothing;smooth bootstrap