A Note on the Properties of Generalised Separable Spatial Autoregressive Process
Spatial modelling has its applications in many fields like geology, agriculture, meteorology, geography, and so forth. In time series a class of models known as Generalised Autoregressive (GAR) has been introduced by Peiris (2003) that includes an index parameter δ. It has been shown that the inclus...
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| Format: | Article |
| Language: | English |
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Wiley
2009-01-01
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| Series: | Journal of Probability and Statistics |
| Online Access: | http://dx.doi.org/10.1155/2009/847830 |
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| author | Mahendran Shitan Shelton Peiris |
| author_facet | Mahendran Shitan Shelton Peiris |
| author_sort | Mahendran Shitan |
| collection | DOAJ |
| description | Spatial modelling has its applications in many fields like geology, agriculture, meteorology, geography, and so forth. In time series a class of models known as Generalised Autoregressive (GAR) has been introduced by Peiris (2003) that includes an index parameter δ. It has been shown that the inclusion of this additional parameter aids in modelling and forecasting many real data sets. This paper studies the properties of a new class of spatial autoregressive process of order 1 with an index. We will call this a Generalised Separable Spatial Autoregressive (GENSSAR) Model. The spectral density function (SDF), the autocovariance function (ACVF), and the autocorrelation function (ACF) are derived. The theoretical ACF and SDF plots are presented as three-dimensional figures. |
| format | Article |
| id | doaj-art-5277ed99c3f54421aa33d1e6129c7724 |
| institution | Kabale University |
| issn | 1687-952X 1687-9538 |
| language | English |
| publishDate | 2009-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Probability and Statistics |
| spelling | doaj-art-5277ed99c3f54421aa33d1e6129c77242025-02-03T05:51:54ZengWileyJournal of Probability and Statistics1687-952X1687-95382009-01-01200910.1155/2009/847830847830A Note on the Properties of Generalised Separable Spatial Autoregressive ProcessMahendran Shitan0Shelton Peiris1Department of Mathematics, Faculty of Science, University Putra Malaysia, 43400 Serdang, MalaysiaSchool of Mathematics and Statistics, The University of Sydney, NSW 2006, AustraliaSpatial modelling has its applications in many fields like geology, agriculture, meteorology, geography, and so forth. In time series a class of models known as Generalised Autoregressive (GAR) has been introduced by Peiris (2003) that includes an index parameter δ. It has been shown that the inclusion of this additional parameter aids in modelling and forecasting many real data sets. This paper studies the properties of a new class of spatial autoregressive process of order 1 with an index. We will call this a Generalised Separable Spatial Autoregressive (GENSSAR) Model. The spectral density function (SDF), the autocovariance function (ACVF), and the autocorrelation function (ACF) are derived. The theoretical ACF and SDF plots are presented as three-dimensional figures.http://dx.doi.org/10.1155/2009/847830 |
| spellingShingle | Mahendran Shitan Shelton Peiris A Note on the Properties of Generalised Separable Spatial Autoregressive Process Journal of Probability and Statistics |
| title | A Note on the Properties of Generalised Separable Spatial Autoregressive Process |
| title_full | A Note on the Properties of Generalised Separable Spatial Autoregressive Process |
| title_fullStr | A Note on the Properties of Generalised Separable Spatial Autoregressive Process |
| title_full_unstemmed | A Note on the Properties of Generalised Separable Spatial Autoregressive Process |
| title_short | A Note on the Properties of Generalised Separable Spatial Autoregressive Process |
| title_sort | note on the properties of generalised separable spatial autoregressive process |
| url | http://dx.doi.org/10.1155/2009/847830 |
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