A Note on the Properties of Generalised Separable Spatial Autoregressive Process
Joint Authors
Peiris, Shelton
Shitan, Mahendran
Source
Journal of Probability and Statistics
Issue
Vol. 2009, Issue 2009 (31 Dec. 2009), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2009-10-08
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Shitan, Mahendran& Peiris, Shelton. 2009. A Note on the Properties of Generalised Separable Spatial Autoregressive Process. Journal of Probability and Statistics،Vol. 2009, no. 2009, pp.1-11.
https://search.emarefa.net/detail/BIM-502993
Modern Language Association (MLA)
Shitan, Mahendran& Peiris, Shelton. A Note on the Properties of Generalised Separable Spatial Autoregressive Process. Journal of Probability and Statistics No. 2009 (2009), pp.1-11.
https://search.emarefa.net/detail/BIM-502993
American Medical Association (AMA)
Shitan, Mahendran& Peiris, Shelton. A Note on the Properties of Generalised Separable Spatial Autoregressive Process. Journal of Probability and Statistics. 2009. Vol. 2009, no. 2009, pp.1-11.
https://search.emarefa.net/detail/BIM-502993
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-502993