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Fractionally Integrated Separable Spatial Autoregressive (FISSAR) Model and Some of Its Properties

Spatial modelling has its applications in many fields. In time-series there exist a class of models known as long memory models where the autocorrelation function decays rather slowly. These types of time-series data are modelled as fractionally integrated ARMA processes. Spatial data may also exhib...

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Main Author: Shitana, Mahendran
Format: Article
Language:English
Published: Taylor & Francis 2008
Online Access:http://psasir.upm.edu.my/id/eprint/7026/
http://dx.doi.org/10.1080/03610920701762762
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spelling my.upm.eprints.70262010-06-02T02:30:34Z http://psasir.upm.edu.my/id/eprint/7026/ Fractionally Integrated Separable Spatial Autoregressive (FISSAR) Model and Some of Its Properties Shitana, Mahendran Spatial modelling has its applications in many fields. In time-series there exist a class of models known as long memory models where the autocorrelation function decays rather slowly. These types of time-series data are modelled as fractionally integrated ARMA processes. Spatial data may also exhibit a long memory structure and in order to model such a structure we introduce a new class of models called the fractionally integrated separable spatial autoregressive (FISSAR) model and discuss some of its properties. One way of estimating the parameters of the FISSAR model is also discussed in this article. Taylor & Francis 2008 Article PeerReviewed Shitana, Mahendran (2008) Fractionally Integrated Separable Spatial Autoregressive (FISSAR) Model and Some of Its Properties. Communications in Statistics: Theory and Methods, 37 (8). pp. 1266-1273. ISSN 1532-415X (online)/0361-0926 (print) http://dx.doi.org/10.1080/03610920701762762 10.1080/03610920701762762 English
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Spatial modelling has its applications in many fields. In time-series there exist a class of models known as long memory models where the autocorrelation function decays rather slowly. These types of time-series data are modelled as fractionally integrated ARMA processes. Spatial data may also exhibit a long memory structure and in order to model such a structure we introduce a new class of models called the fractionally integrated separable spatial autoregressive (FISSAR) model and discuss some of its properties. One way of estimating the parameters of the FISSAR model is also discussed in this article.
format Article
author Shitana, Mahendran
spellingShingle Shitana, Mahendran
Fractionally Integrated Separable Spatial Autoregressive (FISSAR) Model and Some of Its Properties
author_facet Shitana, Mahendran
author_sort Shitana, Mahendran
title Fractionally Integrated Separable Spatial Autoregressive (FISSAR) Model and Some of Its Properties
title_short Fractionally Integrated Separable Spatial Autoregressive (FISSAR) Model and Some of Its Properties
title_full Fractionally Integrated Separable Spatial Autoregressive (FISSAR) Model and Some of Its Properties
title_fullStr Fractionally Integrated Separable Spatial Autoregressive (FISSAR) Model and Some of Its Properties
title_full_unstemmed Fractionally Integrated Separable Spatial Autoregressive (FISSAR) Model and Some of Its Properties
title_sort fractionally integrated separable spatial autoregressive (fissar) model and some of its properties
publisher Taylor & Francis
publishDate 2008
url http://psasir.upm.edu.my/id/eprint/7026/
http://dx.doi.org/10.1080/03610920701762762
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score 13.211869

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