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Author:

Ma, Xuejun (Ma, Xuejun.) | Chen, Xin (Chen, Xin.) | Zhang, Jingxiao (Zhang, Jingxiao.)

Indexed by:

Scopus SCIE

Abstract:

In this paper, we propose a new partial correlation, the so-called composite quantile partial correlation, to measure the relationship of two variables given other variables. We further use this correlation to screen variables in ultrahigh-dimensional varying coefficient models. Our proposed method is fast and robust against outliers and can be efficiently employed in both single index variable and multiple index variable varying coefficient models. Numerical results indicate the preference of our proposed method.

Keyword:

Composite quantile partial correlation robustness multiple index variables

Author Community:

  • [ 1 ] [Ma, Xuejun]Beijing Univ Technol, Coll Appl Sci, Beijing, Peoples R China
  • [ 2 ] [Chen, Xin]Natl Univ Singapore, Dept Stat & Appl Probabil, Singapore, Singapore
  • [ 3 ] [Zhang, Jingxiao]Renmin Univ China, Sch Stat, Ctr Appl Stat, Beijing 100872, Peoples R China

Reprint Author's Address:

  • [Zhang, Jingxiao]Renmin Univ China, Sch Stat, Ctr Appl Stat, Beijing 100872, Peoples R China

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Source :

JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION

ISSN: 0094-9655

Year: 2017

Issue: 4

Volume: 87

Page: 724-732

1 . 2 0 0

JCR@2022

ESI Discipline: MATHEMATICS;

ESI HC Threshold:66

CAS Journal Grade:4

Cited Count:

WoS CC Cited Count: 2

SCOPUS Cited Count: 2

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 4

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