View : 23 Download: 0

Stationary bootstrapping for non-parametric estimator of nonlinear autoregressive model

Title
Stationary bootstrapping for non-parametric estimator of nonlinear autoregressive model
Authors
Hwang E.Shin D.W.
Ewha Authors
신동완황은주
SCOPUS Author ID
신동완scopus
Issue Date
2011
Journal Title
Journal of Time Series Analysis
ISSN
0143-9782JCR Link
Citation
vol. 32, no. 3, pp. 292 - 303
Indexed
SCI; SCIE; SCOPUS WOS scopus
Abstract
We consider stationary bootstrap approximation of the non-parametric kernel estimator in a general kth-order nonlinear autoregressive model under the conditions ensuring that the nonlinear autoregressive process is a geometrically Harris ergodic stationary Markov process. We show that the stationary bootstrap procedure properly estimates the distribution of the non-parametric kernel estimator. A simulation study is provided to illustrate the theory and to construct confidence intervals, which compares the proposed method favorably with some other bootstrap methods. © 2010 Blackwell Publishing Ltd.
DOI
10.1111/j.1467-9892.2010.00699.x
Appears in Collections:
자연과학대학 > 통계학전공 > Journal papers
Files in This Item:
There are no files associated with this item.
Export
RIS (EndNote)
XLS (Excel)
XML


qrcode

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE