Bootstrap for the Sample Mean and for U-Statistics of Mixing and Near Epoch Dependent Processes

Autor:	Sharipov, Olimjon Sh., Wendler, Martin
Rok vydání:	2009
Předmět:	Mathematics - Statistics Theory Mathematics - Probability 62G09 60G10
Druh dokumentu:	Working Paper
Popis:	The validity of various bootstrapping methods has been proved for the sample mean of strongly mixing data. But in many applications, there appear nonlinear statistics of processes that are not strongly mixing. We investigate the nonoverlapping block bootstrap sequences which are near epoch dependent on strong mixing or absolutely regular processes. This includes ARMA and GARCH-processes as well as data from chaotic dynamical systems. We establish the strong consistency of the bootstrap distribution estimator not only for the sample mean, but also for U-statistics, which include examples as Gini's mean difference or the chi^2-test statistic. Comment: 29 pages
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/0911.3083 Zobrazit plný text záznamu View this record from Arxiv