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Title:

High-dimensional sparse vine copula regression with application to genomic prediction

Document type:
Zeitschriftenaufsatz
Author(s):
Sahin, Özge; Czado, Claudia
Abstract:
High-dimensional data sets are often available in genome-enabled predictions. Such data sets include nonlinear relationships with complex dependence structures. For such situations, vine copula based (quantile) regression is an important tool. However, the current vine copula based regression approaches do not scale up to high and ultra-high dimensions. To perform high-dimensional sparse vine copula based regression, we propose two methods. First, we show their superiority regarding computationa...     »
Dewey Decimal Classification:
510 Mathematik
Journal title:
Preprint
Year:
2022
Language:
en
Fulltext / DOI:
doi:10.48550/ARXIV.2208.12383
Publisher:
arXiv
Submitted:
26.08.2022
Semester:
SS 22
TUM Institution:
Professur für Angewandte Mathematische Statistik
Format:
Text
 BibTeX