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Titel:

Membership testing for Bernoulli and tail-dependence matrices

Dokumenttyp:
Zeitschriftenaufsatz
Autor(en):
Krause, D.; Scherer, M.; Schwinn, J.; Werner, R.
Nicht-TUM Koautoren:
ja
Kooperation:
national
Abstract:
Testing a given matrix for membership in the family of Bernoulli matrices is a longstanding problem, the many applications of Bernoulli vectors in computer science, finance, medicine, and operations research emphasize its practical relevance. A novel approach towards this problem was taken by [Fiebig et al., 2017] for low-dimensional settings d≤6. For the first time, they exploit the close relationship between the Bernoulli polytope (also known as correlation polytope) and the we...     »
Stichworte:
Bernoulli-compatible matrix, tail-dependence matrix, column generation, binary quadratic programming
Intellectual Contribution:
Discipline-based Research
Zeitschriftentitel:
Journal of Multivariate Analysis
Journal gelistet in FT50 Ranking:
nein
Jahr:
2018
Jahr / Monat:
2018-11
Monat:
Nov
Heft / Issue:
168
Seitenangaben Beitrag:
240-260
Sprache:
en
Volltext / DOI:
doi:10.1016/j.jmva.2018.07.014
WWW:
https://www.sciencedirect.com/science/article/pii/S0047259X1730564X
TUM Einrichtung:
Lehrstuhl für Finanzmathematik
Urteilsbesprechung:
0
Key publication:
Nein
Peer reviewed:
Ja
commissioned:
not commissioned
Technology:
Nein
Interdisziplinarität:
Nein
Leitbild:
;
Ethics und Sustainability:
Nein
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