摘要
在广义线性模型中,运用Markov inequality等定理,在满足一般规律时,证明了估计方程之间的一些关系;并进一步证明了βn与βn0是渐近相合的.最后运用Lyapunov条件,在满足一般规律的情况下,证明了广义Poisson分布估计量的渐近正态性.以上结果均是在较弱的条件下证明得到,并对相应的结果进行了改进.
In the generalized linear model,some relations between the estimating equations are proved by use of the Markov inequality theorem,and thus it is further proved that βn and βnare of asymptotic consistency.Finally,the asymptotic normality of the estimator of the generalized Poisson distribution is proved by using the Lyapunov condition when the general law is satisfied.These results are proved under the weaker conditions,and the corresponding results are improved.
作者
林松
尹长明
吴迪
LIN Song;YIN Changming;WU Di(School of Mathematics and Information Science,Guangxi University,Nanning,Guangxi 530004,China)
出处
《内江师范学院学报》
2018年第10期39-43,共5页
Journal of Neijiang Normal University
基金
国家自然科学基金(11061002)
广西自然科学基金(2015GXNSFAA139006)
关键词
广义估计方程
Poisson回归模型
高维纵向数据
渐近正态性
generalized estimating equation
poisson regression model
high dimensional longitudinal data
asymptotic normality
