Autoregressive-aided periodogram bootstrap for time series
成果类型：
Article
署名作者：
Kreiss, JP; Paparoditis, E
署名单位：
Braunschweig University of Technology; University of Cyprus
刊物名称：
ANNALS OF STATISTICS
ISSN/ISSBN：
0090-5364
发表日期：
2003
页码：
1923-1955
关键词：
摘要：
A bootstrap methodology for the periodogram of a stationary process is proposed which is based on a combination of a time domain parametric and a frequency domain nonparametric bootstrap. The parametric fit is used to generate periodogram ordinates that imitate the essential features of the data and the weak dependence structure of the periodogram while a nonparametric (kernel-based) correction is applied in order to catch features not represented by the parametric fit. The asymptotic theory developed shows validity of the proposed bootstrap procedure for a large class of periodogram statistics. For important classes of stochastic processes, validity of the new procedure is also established for periodograin statistics not captured by existing frequency domain bootstrap methods based on independent periodogram replicates.