Citation
Abstract
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 . 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.
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Official URL or Download Paper: http://dx.doi.org/10.1155/2009/847830
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Additional Metadata
| Item Type: | Article |
|---|---|
| Divisions: | Faculty of Science Institute for Mathematical Research |
| DOI Number: | https://doi.org/10.1155/2009/847830 |
| Publisher: | Hindawi Publishing Corporation |
| Keywords: | Autoregressive processes; Separable models; Spatial models; GAR models; Time series |
| Depositing User: | Nurul Ainie Mokhtar |
| Date Deposited: | 29 May 2015 08:13 |
| Last Modified: | 03 Feb 2016 03:10 |
| URI: | http://psasir.upm.edu.my/id/eprint/12768 |
| Statistic Details: | View Download Statistic |
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