Further asymptotic properties of the generalized information criterion

被引：2

作者：

Xu, ChangJiang ^{[1
]}

McLeod, A. Ian ^{[1
]}

机构：

[1] Univ Western Ontario, Dept Stat & Actuarial Sci, London, ON N6A 5B7, Canada

来源：

ELECTRONIC JOURNAL OF STATISTICS | 2012年 / 6卷

基金：

加拿大自然科学与工程研究理事会;

关键词：

Variable selection; model selection; information criterion; consistency; VARIABLE SELECTION; REGRESSION; MODEL; SHRINKAGE; NUMBER;

D O I：

10.1214/12-EJS685

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

Asymptotic properties of the generalized information criterion for model selection are examined and new conditions under which this criterion is overfitting, consistent, or underfitting are derived.

引用

页码：656 / 663

页数：8

共 14 条

[1] AKAIKE H, 1979, BIOMETRIKA, V66, P237, DOI 10.1093/biomet/66.2.237
[2] [Anonymous], IEEE T AUTOMATIC CON
[3] Variable selection via nonconcave penalized likelihood and its oracle properties
Fan, JQ
Li, RZ
[J]. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 2001, 96 (456) : 1348 - 1360
[4] Mcquarrie A. D. R., 1998, Regression and time series model selection
[5] ASYMPTOTIC PROPERTIES OF CRITERIA FOR SELECTION OF VARIABLES IN MULTIPLE-REGRESSION
NISHII, R
[J]. ANNALS OF STATISTICS, 1984, 12 (02) : 758 - 765
[6] ESTIMATING DIMENSION OF A MODEL
SCHWARZ, G
[J]. ANNALS OF STATISTICS, 1978, 6 (02) : 461 - 464
[7] Shao J, 1997, STAT SINICA, V7, P221
[8] APPROXIMATE EFFICIENCY OF A SELECTION PROCEDURE FOR THE NUMBER OF REGRESSION VARIABLES
SHIBATA, R
[J]. BIOMETRIKA, 1984, 71 (01) : 43 - 49
[9] Regression shrinkage and selection via the Lasso
Tibshirani, R
[J]. JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 1996, 58 (01) : 267 - 288
[10] NOTE ON THE CONSISTENCY OF THE MAXIMUM LIKELIHOOD ESTIMATE
WALD, A
[J]. ANNALS OF MATHEMATICAL STATISTICS, 1949, 20 (04): : 595 - 601

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