The cumulative Kolmogorov filter for model-free screening in ultrahigh dimensional data

Arlene Kyoung Hee Kim; Seung Jun Shin

doi:10.1016/j.spl.2017.03.012

The cumulative Kolmogorov filter for model-free screening in ultrahigh dimensional data

Arlene Kyoung Hee Kim, Seung Jun Shin

New professors

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

1 Citation (Scopus)

Abstract

We propose a cumulative Kolmogorov filter to improve the fused Kolmogorov filter proposed by Mai and Zou (2015) via cumulative slicing. We establish an improved asymptotic result under relaxed assumptions and numerically demonstrate its enhanced finite sample performance.

Original language	English
Pages (from-to)	238-243
Number of pages	6
Journal	Statistics and Probability Letters
Volume	126
DOIs	https://doi.org/10.1016/j.spl.2017.03.012
Publication status	Published - 2017 Jul 1

Keywords

Cumulative slicing
Kolmogorov filter
Model-free marginal screening

ASJC Scopus subject areas

Statistics and Probability
Statistics, Probability and Uncertainty

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10.1016/j.spl.2017.03.012

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title = "The cumulative Kolmogorov filter for model-free screening in ultrahigh dimensional data",

abstract = "We propose a cumulative Kolmogorov filter to improve the fused Kolmogorov filter proposed by Mai and Zou (2015) via cumulative slicing. We establish an improved asymptotic result under relaxed assumptions and numerically demonstrate its enhanced finite sample performance.",

keywords = "Cumulative slicing, Kolmogorov filter, Model-free marginal screening",

author = "Kim, {Arlene Kyoung Hee} and Shin, {Seung Jun}",

note = "Funding Information: S. J. Shin was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (No. R1C1A1A01054913). Publisher Copyright: {\textcopyright} 2017 Elsevier B.V.",

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AU - Kim, Arlene Kyoung Hee

AU - Shin, Seung Jun

N1 - Funding Information: S. J. Shin was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (No. R1C1A1A01054913). Publisher Copyright: © 2017 Elsevier B.V.

PY - 2017/7/1

Y1 - 2017/7/1

N2 - We propose a cumulative Kolmogorov filter to improve the fused Kolmogorov filter proposed by Mai and Zou (2015) via cumulative slicing. We establish an improved asymptotic result under relaxed assumptions and numerically demonstrate its enhanced finite sample performance.

AB - We propose a cumulative Kolmogorov filter to improve the fused Kolmogorov filter proposed by Mai and Zou (2015) via cumulative slicing. We establish an improved asymptotic result under relaxed assumptions and numerically demonstrate its enhanced finite sample performance.

KW - Cumulative slicing

KW - Kolmogorov filter

KW - Model-free marginal screening

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U2 - 10.1016/j.spl.2017.03.012

DO - 10.1016/j.spl.2017.03.012

M3 - Article

AN - SCOPUS:85017170125

VL - 126

SP - 238

EP - 243

JO - Statistics and Probability Letters

JF - Statistics and Probability Letters

SN - 0167-7152

ER -

The cumulative Kolmogorov filter for model-free screening in ultrahigh dimensional data

Abstract

Keywords

ASJC Scopus subject areas

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