Variable selection in generalized linear models with canonical link functions

被引：5

作者：

Jin, M ^{[1
]}

Fang, YX ^{[1
]}

Zhao, LC ^{[1
]}

机构：

[1] Univ Sci & Technol China, Dept Stat & Finance, Hefei 230026, Peoples R China

来源：

STATISTICS & PROBABILITY LETTERS | 2005年 / 71卷 / 04期

基金：

中国国家自然科学基金;

关键词：

generalized linear model; canonical link function; information theoretic criteria; model selection;

D O I：

10.1016/j.spl.2004.11.021

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：

This paper studies a class of AIC-like model selection criteria for a generalized linear model with the canonical link. They have the form of log L - p * C, where log L is the maximized log-likelihood, p is the number of parameters and C is a term depending on the sample size n and satisfying C/n -> 0 and C/ log log n -> infinity as n -> infinity. Under suitable conditions, this class of criteria is shown to be strongly consistent. A simulation study was also conducted to assess the finite-sample performance with various choices of C for variable selection in a logit model and a log-linear model. (c) 2005 Elsevier B.V. All rights reserved.

引用

页码：371 / 382

页数：12

共 50 条

[41] Structured Variable Selection for Regularized Generalized Canonical Correlation Analysis
Lofstedt, Tommy
Hadj-Selem, Fouad
Guillemot, Vincent
Philippe, Cathy
Duchesnay, Edouard
Frouin, Vincent
Tenenhaus, Arthur
[J]. MULTIPLE FACETS OF PARTIAL LEAST SQUARES AND RELATED METHODS, 2016, 173 : 129 - 139
[42] Using the softplus function to construct alternative link functions in generalized linear models and beyond
Wiemann, Paul F. V.
Kneib, Thomas
Hambuckers, Julien
[J]. STATISTICAL PAPERS, 2024, 65 (05) : 3155 - 3180
[43] ONE DEGREE OF FREEDOM FOR NONADDITIVITY - APPLICATIONS WITH GENERALIZED LINEAR-MODELS AND LINK FUNCTIONS
PETTITT, AN
[J]. BIOMETRICS, 1989, 45 (04) : 1153 - 1162
[44] GENERALIZED LINEAR-MODELS - THE MISSING LINK
COX, C
[J]. JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS, 1984, 33 (01) : 18 - 24
[45] Model Selection in Generalized Linear Models
Mamun, Abdulla
Paul, Sudhir
[J]. SYMMETRY-BASEL, 2023, 15 (10):
[46] Group linear algorithm with sparse principal decomposition: a variable selection and clustering method for generalized linear models
Juan C. Laria
M. Carmen Aguilera-Morillo
Rosa E. Lillo
[J]. Statistical Papers, 2023, 64 : 227 - 253
[47] Group linear algorithm with sparse principal decomposition: a variable selection and clustering method for generalized linear models
Laria, Juan C.
Carmen Aguilera-Morillo, M.
Lillo, Rosa E.
[J]. STATISTICAL PAPERS, 2023, 64 (01) : 227 - 253
[48] A general framework of online updating variable selection for generalized linear models with streaming datasets
Ma, Xiaoyu
Lin, Lu
Gai, Yujie
[J]. JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, 2023, 93 (03) : 325 - 340
[49] Variable selection for generalized varying coefficient partially linear models with diverging number of parameters
Zheng-yan Lin
Yu-ze Yuan
[J]. Acta Mathematicae Applicatae Sinica, English Series, 2012, 28 : 237 - 246
[50] Variable Selection With Prior Information for Generalized Linear Models via the Prior LASSO Method
Jiang, Yuan
He, Yunxiao
Zhang, Heping
[J]. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 2016, 111 (513) : 355 - 376

← 1 2 3 4 5 →