We study the problem of constructing confidence intervals for the long-memory parameter of stationary Gaussian processes with long-range dependence. The focus is on confidence intervals for the wavelet estimator introduced by Abry and Veitch (1998). We propose an approximation to the distribution of the estimator based on subsampling and use it to construct confidence intervals for the long-memory parameter. The performance of these confidence intervals, in terms of both coverage probability and length, is studied by using a Monte Carlo simulation. The proposed confidence intervals have more accurate coverage probability than the method of Abry and Veitch (1999), and are easy to compute in practice. Key words and phrases. Long-range dependence, resampling, wavelets, Hurst parameter.

Confidence intervals for the long memory parameter based on wavelets and resampling / CONTI P., L; DE GIOVANNI, Livia; Stoev, A; Taqqu, M.. - In: STATISTICA SINICA. - ISSN 1017-0405. - 18:2(2008), pp. 559-579.

Confidence intervals for the long memory parameter based on wavelets and resampling

DE GIOVANNI, LIVIA;
2008

Abstract

We study the problem of constructing confidence intervals for the long-memory parameter of stationary Gaussian processes with long-range dependence. The focus is on confidence intervals for the wavelet estimator introduced by Abry and Veitch (1998). We propose an approximation to the distribution of the estimator based on subsampling and use it to construct confidence intervals for the long-memory parameter. The performance of these confidence intervals, in terms of both coverage probability and length, is studied by using a Monte Carlo simulation. The proposed confidence intervals have more accurate coverage probability than the method of Abry and Veitch (1999), and are easy to compute in practice. Key words and phrases. Long-range dependence, resampling, wavelets, Hurst parameter.
Long-range dependence; resampling; wavelets; Hurst parameter
Confidence intervals for the long memory parameter based on wavelets and resampling / CONTI P., L; DE GIOVANNI, Livia; Stoev, A; Taqqu, M.. - In: STATISTICA SINICA. - ISSN 1017-0405. - 18:2(2008), pp. 559-579.
File in questo prodotto:
File Dimensione Formato  
abstractssinica2008.pdf

Solo gestori archivio

Tipologia: Abstract
Licenza: DRM non definito
Dimensione 59.41 kB
Formato Adobe PDF
59.41 kB Adobe PDF   Visualizza/Apri
statsin_08.pdf

Solo gestori archivio

Tipologia: Documento in Post-print
Licenza: DRM non definito
Dimensione 233.95 kB
Formato Adobe PDF
233.95 kB Adobe PDF   Visualizza/Apri
Pubblicazioni consigliate

Caricamento pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11385/6038
Citazioni
  • Scopus 7
  • ???jsp.display-item.citation.isi??? 7
social impact