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Titolo:
Estimating long-range dependence in the presence of periodicity: An empirical study
Autore:
Montanari, A; Taqqu, MS; Teverovsky, V;
Indirizzi:
Politecn Milan, DIIAR, I-20133 Milan, Italy Politecn Milan Milan Italy I-20133 cn Milan, DIIAR, I-20133 Milan, Italy Boston Univ, Dept Math, Boston, MA 02215 USA Boston Univ Boston MA USA 02215 ton Univ, Dept Math, Boston, MA 02215 USA
Titolo Testata:
MATHEMATICAL AND COMPUTER MODELLING
fascicolo: 10-12, volume: 29, anno: 1999,
pagine: 217 - 228
SICI:
0895-7177(199905/06)29:10-12<217:ELDITP>2.0.ZU;2-9
Fonte:
ISI
Lingua:
ENG
Soggetto:
TIME-SERIES;
Keywords:
fractional ARIMA; Hurst parameter; long memory; self-similarity;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Engineering, Computing & Technology
Citazioni:
24
Recensione:
Indirizzi per estratti:
Indirizzo: Montanari, A Politecn Milan, DIIAR, Piazza Leonardo Da Vinci 32, I-20133 Milan, Italy Politecn Milan Piazza Leonardo Da Vinci 32 Milan Italy I-20133
Citazione:
A. Montanari et al., "Estimating long-range dependence in the presence of periodicity: An empirical study", MATH COMP M, 29(10-12), 1999, pp. 217-228

Abstract

Recent results in applied statistics have shown that the presence of periodicity in a time series may have an influence on the estimation of the longmemory (long-range dependence) parameter H. In particular, some estimatorsfalsely detect the presence of long-range dependence when periodicity is present. In this paper, we apply various estimation procedures to synthetic periodic time series in order to verify the performance of each estimation method and to determine which estimators should be used when periodicity may be present. (C) 1999 Elsevier Science Ltd. All rights reserved.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 25/09/20 alle ore 13:40:47