Bootstrap for the sample mean and forU-statistics of mixing and near-epoch dependent processes

Autor:	Martin Wendler, Olimjon Sh. Sharipov
Rok vydání:	2012
Předmět:	Statistics and Probability Nonlinear system Heteroscedasticity Bootstrapping (electronics) Statistics Strong consistency Estimator Statistics Probability and Uncertainty Statistic Mixing (physics) Block (data storage) Mathematics
Zdroj:	Journal of Nonparametric Statistics. 24:317-342
ISSN:	1029-0311 1048-5252
DOI:	10.1080/10485252.2012.655274
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 linear processes and conditional heteroskedastic 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 such examples as Gini's mean difference or the χ2-test statistic.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::69bacbfe5f4c194d6139a73154acef15 https://doi.org/10.1080/10485252.2012.655274 Zobrazit plný text záznamu