Please use this identifier to cite or link to this item:
https://hdl.handle.net/10216/99212
Author(s): | Isabel Silva M. Eduarda Silva |
Title: | Parameter estimation for INAR processes based on high-order statistics |
Issue Date: | 2008 |
Abstract: | 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, models 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 model, based on Least Squares applied on 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. |
Subject: | Estatística, Matemática Statistics, Mathematics |
Scientific areas: | Ciências exactas e naturais::Matemática Natural sciences::Mathematics |
URI: | https://repositorio-aberto.up.pt/handle/10216/99212 |
Source: | COMPSTAT 2008 - Proceedings in Computational Statistics |
Document Type: | Capítulo ou Parte de Livro |
Rights: | restrictedAccess |
Appears in Collections: | FEP - Capítulo ou Parte de Livro FEUP - Capítulo ou Parte de Livro |
Files in This Item:
File | Description | Size | Format | |
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57902.pdf Restricted Access | 165.21 kB | Adobe PDF | Request a copy from the Author(s) |
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