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Statistical inference for quantile correlation regression with bivariate outcomes — arXiv:2610.41126

Source: arXiv (en)
Original: https://arxiv.org/abs/2610.41126
License (as archived): CC0-1.0
Archived: 2026-11-03T05:42:27.635Z
SHA-256 of the archived text: 768d39eeede43376f99f789d03091483a1d31042207901b626065e8b9c86803d
Stable URL of this page: https://metraipolis.com/documento/dc_dce425df65db

How to cite

Statistical inference for quantile correlation regression with bivariate outcomes — arXiv:2610.41126 — arXiv (en), https://arxiv.org/abs/2610.41126 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_dce425df65db (Metraipolis archive dc_dce425df65db, sha256 768d39eeede43376f99f789d03091483a1d31042207901b626065e8b9c86803d)

BibTeX

@misc{dcdce425df65db,
  title = {Statistical inference for quantile correlation regression with bivariate outcomes — arXiv:2610.41126},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2610.41126},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_dce425df65db; sha256 768d39eeede43376f99f789d03091483a1d31042207901b626065e8b9c86803d},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2610.41126. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

It is increasing scientifically important to recognize, quantify and visualize the dependence structure between the bivariate outcomes. In this paper, we investigate conditional dependence using a new dependence measure, the quantile correlation coefficient, which is defined by the Pearson correlation of two quantile-hits of bivariate outcomes. Furthermore, we propose a new regression model for covariate effects directly on the quantile correlation coefficient via a generalized linear regression model. The proposed model has intuitive interpretation and provides a comprehensive view of covariate effects across quantiles of bivariate outcomes. The proposed estimator enjoys desirable asymptotic properties including uniform consistency and weak convergence as a process in the quantile index. Additionally, we develop the general hypothesis testing for the regression coefficients, with applications to summarize covariate effects across the quantile ranges. Simulation studies demonstrate the good finite sample performance of the proposed estimation and inference procedures. Two empirical applications of the proposed method reveal interesting insights in premature twins data for measuring association and ChIP-seq data for measuring reproducibility.

Tema degli esploratori: statistica e scienza dei dati (elenco arXiv stat.ME, nuovi lavori del giorno).
Categorie arXiv: Methodology (stat.ME).
Pagina del lavoro: https://arxiv.org/abs/2610.41126 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-11-03T05:27:12.810Z dalla pagina https://arxiv.org/list/stat.ME/new (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).