Decomposition of discrete time periodically correlated and multivariate stationary symmetric stable processes
The spectral structure of discrete time periodically correlated (as well as multivariate stationary) symmetric [alpha]-stable processes is identified by decomposing such a process uniquely in distribution into one sum of three mutually independent periodically correlated (multivariate stationary) stable processes that are classified as mixed moving average, harmonizable and of a third kind. The techniques are based on presenting the flow and its cocycle that govern the spectral representation of the process, using the Hopf decomposition and specifying the harmonizable component.
Year of publication: |
2005
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Authors: | Soltani, A.R. ; Parvardeh, A. |
Published in: |
Stochastic Processes and their Applications. - Elsevier, ISSN 0304-4149. - Vol. 115.2005, 11, p. 1838-1859
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Publisher: |
Elsevier |
Keywords: | Periodically correlated stable processes Multivariate stationary stable processes Spectral representation Mixed moving average Periodically correlated harmonizable processes Flow Cocycle Hopf decomposition |
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