Corrected T(q)-Likelihood Estimator in a Generalized Linear Structural Regression Model with Measurement Errors

被引：0
|
作者：
A. V. Savchenko
机构：
[1] Eastern Ukraine State University,
来源：
Ukrainian Mathematical Journal | 2015年 / 66卷
关键词：
Maximum Likelihood Estimator; Likelihood Estimator; Asymptotic Normality; Dispersion Parameter; Strong Consistency;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
We study a generalized linear structural regression model with measurement errors. The dispersion parameter is assumed to be known. The corrected T (q) -likelihood estimator for the regression coefficients is constructed. In the case where q depends on the sample size and approaches 1 as the sample size infinitely increases, we establish sufficient conditions or the strong consistency and asymptotic normality of the estimator.
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页码：1823 / 1841
页数：18
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