Finite-Sample Properties of the Maximum Likelihood Estimator for the Poisson Regression Model With Random Covariates

被引：4

作者：

Chen, Qian ^{[2
]}

Giles, David E. ^{[1
]}

机构：

[1] Univ Victoria, Dept Econ, STN CSC, Victoria, BC V8W 2Y2, Canada

[2] Cent Univ Finance & Econ, Sch Publ Finance & Publ Policy, Beijing, Peoples R China

来源：

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2011年 / 40卷 / 06期

关键词：

Bias; Bias correction; Mean squared error; Poisson regression model; Random covariates; MEAN SQUARED ERROR; 2ND-ORDER BIAS; TESTS;

D O I：

10.1080/03610920903506587

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：

We examine the small-sample behaviour of the maximum likelihood estimator for the Poisson regression model with random covariates. Analytic expressions for the second-order bias and mean squared error are derived, and we undertake some numerical evaluations to illustrate these results for the single covariate case. The properties of the bias-adjusted maximum likelihood estimator are investigated in a Monte Carlo experiment. Correcting the estimator for its second-order bias is found to be effective in the cases considered, and we recommend its use when the Poisson regression model is estimated by maximum likelihood with small samples. © 2010 Taylor & Francis Group, LLC.

引用

页码：1000 / 1014

页数：15

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