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Smooth bootstrapping of copula functionals

Coblenz, Maximilian; Grothe, Oliver 1; Herrmann, Klaus; Hofert, Marius
1 Institut für Operations Research (IOR), Karlsruher Institut für Technologie (KIT)

Abstract:

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.


Verlagsausgabe §
DOI: 10.5445/IR/1000146545
Veröffentlicht am 18.05.2022
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Operations Research (IOR)
Publikationstyp Zeitschriftenaufsatz
Publikationsdatum 01.01.2022
Sprache Englisch
Identifikator ISSN: 1935-7524
KITopen-ID: 1000146545
Erschienen in Electronic Journal of Statistics
Verlag Institute of Mathematical Statistics (IMS)
Band 16
Heft 1
Seiten 2550-2606
Nachgewiesen in Dimensions
Web of Science
Scopus
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