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| Asymptotic normality and strong consistency of maximum quasi-likelihood estimates in generalized linear models | |
| 作者姓名： | YIN Changming ZHAO Lincheng & WEI Chengdong School of Mathematics and Information Science Guangxi University Manning China |
| 作者单位： | YIN Changming，ZHAO Lincheng & WEI Chengdong School of Mathematics and Information Science，Guangxi University，Manning 530004，China; Department of Statistics and Finance，University of Science and Technology of China，Hefei 230026，China; Department of Mathematics，Guangxi Teacher College，Manning 530001，China; |
| 摘 要： | In a generalized linear model with q x 1 responses, the bounded and fixed (or adaptive) p × q regressors Zi and the general link function, under the most general assumption on the minimum eigenvalue of ZiZ'i,the moment condition on responses as weak as possible and the other mild regular conditions, we prove that the maximum quasi-likelihood estimates for the regression parameter vector are asymptotically normal and strongly consistent. |
| 收稿时间： | 7 July 2004 |
| 修稿时间： | 7 June 2005 |
Asymptotic normality and strong consistency of maximum quasi-likelihood estimates in generalized linear models |
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| YIN Changming,ZHAO Lincheng & WEI Chengdong School of Mathematics and Information Science,Guangxi University,Manning ,China,.Asymptotic normality and strong consistency of maximum quasi-likelihood estimates in generalized linear models[J].Science in China(Mathematics),2006,49(2):145-157. | |
| Authors: | YIN Changming ZHAO Lincheng WEI Chengdong |
| Institution: | 1. School of Mathematics and Information Science, Guangxi University, Nanning 530004, China;Department of Statistics and Finance, University of Science and Technology of China, Hefei 230026 China 2. Department of Statistics and Finance, University of Science and Technology of China, Hefei 230026 China 3. Department of Mathematics, Guangxi Teacher College, Nanning 530001, China |
| Abstract: | In a generalized linear model with q × 1 responses, the bounded and fixed (or adaptive) p × q regressors Z i and the general link function, under the most general assumption on the minimum eigenvalue of Σ e=1 n Z i Z′ i , the moment condition on responses as weak as possible and the other mild regular conditions, we prove that the maximum quasi-likelihood estimates for the regression parameter vector are asymptotically normal and strongly consistent. |
| Keywords: | generalized linear models quasi-likelihood estimates asymptotic normality strong consistency |
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