W-transforms: Uniformity-preserving transformations and induced dependence structures

Fuente: arXiv
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Main Authors: Hofert, Marius, Pang, Zhiyuan
Format: Preprint
Published: 2025
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author Hofert, Marius
Pang, Zhiyuan
author_facet Hofert, Marius
Pang, Zhiyuan
contents W-transforms are introduced as uniformity-preserving univariate transformations on the unit interval induced by distribution functions and piecewise strictly monotone functions, and their properties are investigated. When applied componentwise to random vectors with standard uniform univariate margins, W-transforms naturally serve as copula-to-copula transformations. Properties of the resulting W-transformed copulas, including their analytical form, density, measures of concordance, tail dependence and symmetries, are derived. A flexible parametric family of W-transforms is proposed as a special case to further enhance tractability. Illustrative examples highlight the introduced concepts, and improved dependence modelling is demonstrated in terms of a real-life dataset.
format Preprint
id arxiv_https___arxiv_org_abs_2509_26280
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle W-transforms: Uniformity-preserving transformations and induced dependence structures
Hofert, Marius
Pang, Zhiyuan
Methodology
Probability
62H99, 60E05, 62E15, 62H20
W-transforms are introduced as uniformity-preserving univariate transformations on the unit interval induced by distribution functions and piecewise strictly monotone functions, and their properties are investigated. When applied componentwise to random vectors with standard uniform univariate margins, W-transforms naturally serve as copula-to-copula transformations. Properties of the resulting W-transformed copulas, including their analytical form, density, measures of concordance, tail dependence and symmetries, are derived. A flexible parametric family of W-transforms is proposed as a special case to further enhance tractability. Illustrative examples highlight the introduced concepts, and improved dependence modelling is demonstrated in terms of a real-life dataset.
title W-transforms: Uniformity-preserving transformations and induced dependence structures
topic Methodology
Probability
62H99, 60E05, 62E15, 62H20
url https://arxiv.org/abs/2509.26280