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dc.creatorIsabel Silva
dc.creatorM. Eduarda Silva
dc.description.abstractThe 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.
dc.subjectEstatística, Matemática
dc.subjectStatistics, Mathematics
dc.titleParameter estimation for INAR processes based on high-order statistics
dc.typeArtigo em Revista Científica Internacional
dc.contributor.uportoFaculdade de Engenharia
dc.contributor.uportoFaculdade de Ciências
dc.subject.fosCiências exactas e naturais::Matemática
dc.subject.fosNatural sciences::Mathematics
Appears in Collections:FCUP - Artigo em Revista Científica Internacional
FEUP - Artigo em Revista Científica Internacional

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