Estimating long-range dependence in the presence of periodicity: An empirical study

Authors:
A. Montanari;M. S. Taqqu;V. Teverovsky
Affiliations:
DIIAR, Politecnico di Milano, Piazza Leonardo da Vinci 32 I-20133 Milano, Italy;Department of Mathematics, Boston University, 111 Cummington Street Boston, MA 02215, U.S.A.;Department of Mathematics, Boston University, 111 Cummington Street Boston, MA 02215, U.S.A.
Venue:
Mathematical and Computer Modelling: An International Journal
Year:
1999

Citing 2
Cited 0

Time series: theory and methods

Time series: theory and methods
Approach to an irregular time series on the basis of the fractal theory

Physica D

Quantified Score

Hi-index	0.98

Visualization

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 long memory (long-range dependence) parameter H. In particular, some estimators falsely 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.