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Diagnostics in generalized nonlinear models based on maximum L_q-likelihood estimation 被引量:1
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作者 徐伟娟 林金官 《Journal of Southeast University(English Edition)》 EI CAS 2013年第1期106-110,共5页
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 Lq-likelihood e... 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 Lq-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 Lq-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 Lq-likelihood method than those through the maximum likelihood estimation method. 展开更多
关键词 maximum lq-likelihood estimation generalized nonlinear regression model case-deletion model generalized Cook distance likelihood distance difference of deviance
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