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Title:

Membership testing for Bernoulli and tail-dependence matrices

Document type:
Zeitschriftenaufsatz
Author(s):
Krause, D.; Scherer, M.; Schwinn, J.; Werner, R.
Non-TUM Co-author(s):
ja
Cooperation:
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...     »
Keywords:
Bernoulli-compatible matrix, tail-dependence matrix, column generation, binary quadratic programming
Intellectual Contribution:
Discipline-based Research
Journal title:
Journal of Multivariate Analysis
Journal listet in FT50 ranking:
nein
Year:
2018
Year / month:
2018-11
Month:
Nov
Journal issue:
168
Pages contribution:
240-260
Language:
en
Fulltext / DOI:
doi:10.1016/j.jmva.2018.07.014
WWW:
https://www.sciencedirect.com/science/article/pii/S0047259X1730564X
TUM Institution:
Lehrstuhl für Finanzmathematik
Judgement review:
0
Key publication:
Nein
Peer reviewed:
Ja
Commissioned:
not commissioned
Technology:
Nein
Interdisciplinarity:
Nein
Mission statement:
;
Ethics and Sustainability:
Nein
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