Jackknife empirical likelihood

Bing Yi Jing; Junqing Yuan; Wang Zhou

doi:10.1198/jasa.2009.tm08260

Jackknife empirical likelihood

Bing Yi Jing^*, Junqing Yuan, Wang Zhou

^*Corresponding author for this work

Department of Mathematics

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

190 Citations (Scopus)

Abstract

Empirical likelihood has been found very useful in many different occasions. However, when applied directly to some more complicated statistics such as U-statistics, it runs into serious computational difficulties. In this paper, we introduce a so-called jackknife empirical likelihood (JEL) method. The new method is extremely simple to use in practice. In particular, the JEL is shown to be very effective in handling one and two-sample U-statistics. The JEL can be potentially useful for other nonlinear statistics.

Original language	English
Pages (from-to)	1224-1232
Number of pages	9
Journal	Journal of the American Statistical Association
Volume	104
Issue number	487
DOIs	https://doi.org/10.1198/jasa.2009.tm08260
Publication status	Published - Sept 2009

Keywords

Confidence regions
Empirical likelihood
Jackknife
Pseudo-values
U-statistics

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title = "Jackknife empirical likelihood",

abstract = "Empirical likelihood has been found very useful in many different occasions. However, when applied directly to some more complicated statistics such as U-statistics, it runs into serious computational difficulties. In this paper, we introduce a so-called jackknife empirical likelihood (JEL) method. The new method is extremely simple to use in practice. In particular, the JEL is shown to be very effective in handling one and two-sample U-statistics. The JEL can be potentially useful for other nonlinear statistics.",

keywords = "Confidence regions, Empirical likelihood, Jackknife, Pseudo-values, U-statistics",

author = "Jing, \{Bing Yi\} and Junqing Yuan and Wang Zhou",

year = "2009",

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TY - JOUR

T1 - Jackknife empirical likelihood

AU - Jing, Bing Yi

AU - Yuan, Junqing

AU - Zhou, Wang

PY - 2009/9

Y1 - 2009/9

N2 - Empirical likelihood has been found very useful in many different occasions. However, when applied directly to some more complicated statistics such as U-statistics, it runs into serious computational difficulties. In this paper, we introduce a so-called jackknife empirical likelihood (JEL) method. The new method is extremely simple to use in practice. In particular, the JEL is shown to be very effective in handling one and two-sample U-statistics. The JEL can be potentially useful for other nonlinear statistics.

AB - Empirical likelihood has been found very useful in many different occasions. However, when applied directly to some more complicated statistics such as U-statistics, it runs into serious computational difficulties. In this paper, we introduce a so-called jackknife empirical likelihood (JEL) method. The new method is extremely simple to use in practice. In particular, the JEL is shown to be very effective in handling one and two-sample U-statistics. The JEL can be potentially useful for other nonlinear statistics.

KW - Confidence regions

KW - Empirical likelihood

KW - Jackknife

KW - Pseudo-values

KW - U-statistics

UR - https://www.scopus.com/pages/publications/70349774775

U2 - 10.1198/jasa.2009.tm08260

DO - 10.1198/jasa.2009.tm08260

M3 - Journal Article

SN - 0162-1459

VL - 104

SP - 1224

EP - 1232

JO - Journal of the American Statistical Association

JF - Journal of the American Statistical Association

IS - 487

ER -

Jackknife empirical likelihood

Abstract

Keywords

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