TY - JOUR
T1 - Variable selection in generalized linear models with canonical link functions
AU - Jin, Man
AU - Fang, Yixin
AU - Zhao, Lincheng
N1 - Funding Information:
Research partially supported by National Natural Science Foundation of China (Grant no. 10471136), Ph.D. Program Foundation of the Ministry of Education of China, and Special Foundations of the Chinese Academy of Science and USTC.
PY - 2005/3/15
Y1 - 2005/3/15
N2 - 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 → ∞ as n → ∞. 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.
AB - 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 → ∞ as n → ∞. 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.
KW - Canonical link function
KW - Generalized linear model
KW - Information theoretic criteria
KW - Model selection
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U2 - 10.1016/j.spl.2004.11.021
DO - 10.1016/j.spl.2004.11.021
M3 - Article
AN - SCOPUS:14544272389
SN - 0167-7152
VL - 71
SP - 371
EP - 382
JO - Statistics and Probability Letters
JF - Statistics and Probability Letters
IS - 4
ER -