[1]陈卓恒.负二项分布的广义线性模型及其应用[J].华侨大学学报(自然科学版),2011,32(2):226-230.[doi:10.11830/ISSN.1000-5013.2011.02.0226]
　CHEN Zhuo-heng.Generalized Linear Model Based on Negative Binomial Distribution and Its Application[J].Journal of Huaqiao University(Natural Science),2011,32(2):226-230.[doi:10.11830/ISSN.1000-5013.2011.02.0226]
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负二项分布的广义线性模型及其应用()
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《华侨大学学报（自然科学版）》[ISSN:1000-5013/CN:35-1079/N]

卷:
第32卷
期数:
2011年第2期
页码:
226-230
栏目:
出版日期:
2011-03-20

文章信息/Info

Title:
Generalized Linear Model Based on Negative Binomial Distribution and Its Application
文章编号:
1000-5013(2011)02-0226-05
作者:
陈卓恒
华侨大学数学科学学院
Author(s):
CHEN Zhuo-heng
School of Mathematical Sciences, Huaqiao University, Quanzhou 362021, China
关键词:
负二项分布;  广义线性模型;  Wald检验;  风险分级
Keywords:
negative binomial distribution;  generalized linear model;  wald test;  risk classification
分类号:
O211.3
DOI:
10.11830/ISSN.1000-5013.2011.02.0226
文献标志码:
A
摘要:
讨论一类散度偏大的分布负二项分布的相关性质,以服从负二项分布的索赔次数为响应变量,引入风险分级变量和对数联结函数,建立广义线性模型.采用极大似然估计法进行参数估计,并用Wald检验法进行检验.最后,利用SAS软件包对一组保险索赔数据进行实证分析.
Abstract:
The properties of the negative binomial distribution which is over-dispersion is discussed in the paper.A generalized linear model which based on the distribution is intruduced.The maximum likelihood estimates and wald test for the model are considered.At last the model is applied to a real data set of aggregate claims for automobile insurance using SAS package.

参考文献/References:

[1] SUSANNE G, CLAUDIA C. Modelling count data with overdispersion and spatial effects [J]. Statistical Papers, 2008(3):531-552.
[2] 田霆, 刘次华. 定时截尾缺失数据下指数分布的参数AMLE [J]. 华侨大学学报(自然科学版), 2006(4):351-353.doi:10.3969/j.issn.1000-5013.2006.04.004.
[3] FAHRMEIR L, THTZ G. Multivariate statistical modelling based on generalized linear models [M]. New York:springer-verlag, 1996.
[4] 毛泽春, 刘锦萼. 一类索赔次数的回归模型及其在风险分级中的应用 [J]. 应用概率统计, 2004(4):359-367.doi:10.3969/j.issn.1001-4268.2004.04.004.
[5] MCCULLAGH P, NELDER J A. Generalized linear models [M]. London:Chapman and Hall, 1989.

备注/Memo

备注/Memo:
华侨大学科研基金资助项目(07HZR04)
更新日期/Last Update: 2014-03-23