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Parameter estimation for INAR processes based on high-order statistics

Title
Parameter estimation for INAR processes based on high-order statistics
Type
Article in International Scientific Journal
Year
2009
Authors
Isabel Silva
(Author)
FEUP
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M. Eduarda Silva
(Author)
FCUP
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Journal
Vol. 7 No. 2
Pages: 105-117
ISSN: 1645-6726
Scientific classification
FOS: Natural sciences > Mathematics
CORDIS: Physical sciences > Mathematics > Statistics
Other information
Authenticus ID: P-003-MC3
Abstract (EN): The high-order statistics (moments and cumulants of order higher than two) have been widely applied in several fields, specially in problems where it is conjectured a lack of Gaussianity and/or non-linearity. Since the INteger-valued AutoRegressive, INAR, processes are non-Gaussian, the high-order statistics can provide additional information that allows a better characterization of these processes. Thus, an estimation method for the parameters of an INAR process, based on Least Squares for the third-order moments is proposed. The results of a Monte Carlo study to investigate the performance of the estimator are presented and the method is applied to a set of real data.
Language: English
Type (Professor's evaluation): Scientific
Contact: ims@fe.up.pt; mesilva@fep.up.pt
No. of pages: 13
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