Covariance matrix of the bias-corrected maximum likelihood estimator in generalized linear models

被引：1

作者：

Cordeiro, Gauss M. ^{[1
]}

Botter, Denise A. ^{[2
]}

Cavalcanti, Alexsandro B. ^{[3
]}

Barroso, Lucia P. ^{[2
]}

机构：

[1] Univ Fed Pernambuco, Dept Estat, BR-50740540 Recife, PE, Brazil

[2] Univ Sao Paulo, Dept Estat, BR-05508090 Sao Paulo, Brazil

[3] Univ Fed Campina Grande, Dept Matemat & Estat, BR-58109970 Campina Grande, PB, Brazil

来源：

STATISTICAL PAPERS | 2014年 / 55卷 / 03期

基金：

巴西圣保罗研究基金会;

关键词：

Bias estimator; Covariance matrix; Generalized linear model; Wald test; 2ND-ORDER;

D O I：

10.1007/s00362-013-0514-1

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：

For the first time, we obtain a general formula for the asymptotic covariance matrix of the bias-corrected maximum likelihood estimators of the linear parameters in generalized linear models, where is the sample size. The usefulness of the formula is illustrated in order to obtain a better estimate of the covariance of the maximum likelihood estimators and to construct better Wald statistics. Simulation studies and an application support our theoretical results.

引用

页码：643 / 652

页数：10

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