Inference for semiparametric Gaussian copula model adjusted for linear regression using residual ranks

Yue Zhao; Irène Gijbels; Ingrid van Keilegom

Inference for semiparametric Gaussian copula model adjusted for linear regression using residual ranks

Yue Zhao, Irène Gijbels, Ingrid van Keilegom

Mathematics

Research output: Contribution to journal › Article › peer-review

Original language	English
Pages (from-to)	2815-2846
Number of pages	32
Journal	Bernoulli
Volume	26
Issue number	4
Publication status	Published - 1 Nov 2020

Bibliographical note

This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details.

Access to Document

BEJ1904-026R2A0
This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details.
Accepted author manuscript, 854 KB

Cite this

@article{6850b39d240d4f5f8069b1bf9ca671e9,

title = "Inference for semiparametric Gaussian copula model adjusted for linear regression using residual ranks",

author = "Yue Zhao and Ir{\`e}ne Gijbels and {van Keilegom}, Ingrid",

note = "This is an author-produced version of the published paper. Uploaded in accordance with the publisher{\textquoteright}s self-archiving policy. Further copying may not be permitted; contact the publisher for details.",

year = "2020",

month = nov,

day = "1",

language = "English",

volume = "26",

pages = "2815--2846",

journal = "Bernoulli",

issn = "1350-7265",

publisher = "International Statistical Institute",

number = "4",

}

TY - JOUR

T1 - Inference for semiparametric Gaussian copula model adjusted for linear regression using residual ranks

AU - Zhao, Yue

AU - Gijbels, Irène

AU - van Keilegom, Ingrid

N1 - This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details.

PY - 2020/11/1

Y1 - 2020/11/1

M3 - Article

VL - 26

SP - 2815

EP - 2846

JO - Bernoulli

JF - Bernoulli

SN - 1350-7265

IS - 4

ER -