A functional limit theorem for η-weakly dependent processes and its applications

被引：0
|
作者：
Bardet J.-M. [1 ]
Doukhan P. [1 ,2 ]
León J.R. [3 ]
机构：
[1] CES, Équipe SAMOS-MATISSE, Université Paris I, Paris 75013
[2] LS-CREST, Timbre J340, Malakoff 92240
[3] Universidad Central de Venezuela, Escuela de Matemática, Los Chaguaramos, Caracas 1041
来源：
Statistical Inference for Stochastic Processes | 2008年 / 11卷 / 3期
关键词：
Central limit theorem; Sample moments and cumulants; Weakly dependent processes;
D O I：
10.1007/s11203-007-9015-y
中图分类号：
学科分类号：
摘要：
We prove a general functional central limit theorem for weak dependent time series. A very large variety of models, for instance, causal or non causal linear, ARCH(∞), LARCH(∞), Volterra processes, satisfies this theorem. Moreover, it provides numerous applications as well for bounding the distance between the empirical mean and the Gaussian measure than for obtaining central limit theorem for sample moments and cumulants. © 2007 Springer Science+Business Media B.V.
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页码：265 / 280
页数：15
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