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Computation and Characterization of Autocorrelations and Partial Autocorrelations in Periodic ARMA Models.
- Source :
-
Journal of Time Series Analysis . May2004, Vol. 25 Issue 3, p359-372. 14p. - Publication Year :
- 2004
-
Abstract
- This paper studies correlation and partial autocorrelation properties of periodic autoregressive moving-average (PARMA) time series models. An efficient algorithm to compute PARMA autocovariances is first derived. An innovations based algorithm to compute partial autocorrelations for a general periodic series is then developed. Finally, periodic moving averages and autoregressions are characterized as periodically stationary series whose autocovariances and partial autocorrelations, respectively, are zero at all lags that exceed some periodically varying threshold. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 01439782
- Volume :
- 25
- Issue :
- 3
- Database :
- Academic Search Index
- Journal :
- Journal of Time Series Analysis
- Publication Type :
- Academic Journal
- Accession number :
- 13112165
- Full Text :
- https://doi.org/10.1111/j.1467-9892.2004.00356.x