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Titel:

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

Dokumenttyp:
Zeitschriftenaufsatz
Autor(en):
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 Dezimalklassifikation:
510 Mathematik
Zeitschriftentitel:
Preprint
Jahr:
2022
Sprache:
en
Volltext / DOI:
doi:10.48550/ARXIV.2208.12383
Verlag / Institution:
arXiv
Eingereicht (bei Zeitschrift):
26.08.2022
Semester:
SS 22
TUM Einrichtung:
Professur für Angewandte Mathematische Statistik
Format:
Text
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