confidenceintervalsofvariancefunctionsingeneralizedlinearmodel

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	confidenceintervalsofvariancefunctionsingeneralizedlinearmodel
	Yong Zhou; Daoji Li
	2006
发表期刊	actamathematicaeapplicataesinica
ISSN	0168-9673
卷号	22 期号:3 页码:353
摘要	In this paper we introduce an appealing nonparametric method for estimating variance and conditional variance functions in generalized linear models （GLMs）, when designs are fixed points and random variables respectively, Bias-corrected confidence bands are proposed for the （conditional） variance by local linear smoothers. Nonparametric techniques are developed in deriving the bias-corrected confidence intervals of the （conditional） variance. The asymptotic distribution of the proposed estimator is established and show that the bias-corrected confidence bands asymptotically have the correct coverage properties. A small simulation is performed when unknown regression parameter is estimated by nonparametric quasi-likelihood. The results are also applicable to nonparamctric autoregressive times series model with heteroscedastic conditional variance.
语种	英语
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/45648
专题	应用数学研究所
作者单位	中国科学院数学与系统科学研究院
推荐引用方式 GB/T 7714	Yong Zhou,Daoji Li. confidenceintervalsofvariancefunctionsingeneralizedlinearmodel[J]. actamathematicaeapplicataesinica,2006,22(3):353.
APA	Yong Zhou,&Daoji Li.(2006).confidenceintervalsofvariancefunctionsingeneralizedlinearmodel.actamathematicaeapplicataesinica,22(3),353.
MLA	Yong Zhou,et al."confidenceintervalsofvariancefunctionsingeneralizedlinearmodel".actamathematicaeapplicataesinica 22.3(2006):353.