[1] Xu Weijuan, Lin Jinguan,. Diagnostics in generalized nonlinear modelsbased on maximum Lqq-likelihood estimation [J]. Journal of Southeast University (English Edition), 2013, 29 (1): 106-110. [doi:10.3969/j.issn.1003-7985.2013.01.022]
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Diagnostics in generalized nonlinear modelsbased on maximum Lqq-likelihood estimation(
)
基于最大Lqq似然估计的广义非线性模型的统计诊断
)Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]
- Volumn:
- 29
- Issue:
- 2013 1
- Page:
- 106-110
- Research Field:
- Mathematics, Physics, Mechanics
- Publishing date:
- 2013-03-20
Info
- Title:
- Diagnostics in generalized nonlinear modelsbased on maximum Lqq-likelihood estimation
- 基于最大Lqq似然估计的广义非线性模型的统计诊断
- Author(s):
- Xu Weijuan; Lin Jinguan
- Department of Mathematics, Southeast University, Nanjing 211189, China
- Keywords:
- maximum Lqq-likelihood estimation; generalized nonlinear regression model; case-deletion model; generalized Cook distance; likelihood distance; difference of deviance
- PACS:
- O212.4
- DOI:
- 10.3969/j.issn.1003-7985.2013.01.022
- Abstract:
- In order to detect whether the data conforms to the given model, it is necessary to diagnose the data in the statistical way. The diagnostic problem in generalized nonlinear models based on the maximum Lqq-likelihood estimation is considered. Three diagnostic statistics are used to detect whether the outliers exist in the data set. Simulation results show that when the sample size is small, the values of diagnostic statistics based on the maximum Lqq-likelihood estimation are greater than the values based on the maximum likelihood estimation. As the sample size increases, the difference between the values of the diagnostic statistics based on two estimation methods diminishes gradually. It means that the outliers can be distinguished easier through the maximum Lqq-likelihood method than those through the maximum likelihood estimation method.
- 为了检测数据是否符合给定的模型, 需要对数据进行统计诊断.研究了基于最大Lqq似然估计的广义非线性模型的统计诊断问题.利用3个统计诊断量来检验数据中是否都存在异常点.模拟结果显示, 当样本容量较小时, 使用最大Lqq似然估计方法得到的诊断统计量的结果要比使用极大似然估计(MLE)方法得到的结果大;随着样本容量的增加, 它们之间的区别逐渐减小.因此, 使用最大Lqq似然估计方法比用MLE方法更容易找到数据中的异常点.
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Memo
- Memo:
-
Biographies: Xu Weijuan(1977—), female, graduate; Lin Jinguan(corresponding author), male, doctor, professor, jglin@seu.edu.cn.
Foundation items: The National Natural Science Foundation of China(No.11171065), the Natural Science Foundation of Jiangsu Province(No.BK2011058).
Citation: Xu Weijuan, Lin Jinguan.Diagnostics in generalized nonlinear models based on maximum Lqq-likelihood estimation[J].Journal of Southeast University(English Edition), 2013, 29(1):106-110.[doi:10.3969/j.issn.1003-7985.2013.01.022]