A stochastic neighborhood conditional auto-regressive model for spatial data

White, Gentry and Ghosh, Sujit K. (2009) A stochastic neighborhood conditional auto-regressive model for spatial data. Computational Statistics & Data Analysis, 53 8: 3033-3046. doi:10.1016/j.csda.2008.08.010

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Author White, Gentry
Ghosh, Sujit K.
Title A stochastic neighborhood conditional auto-regressive model for spatial data
Journal name Computational Statistics & Data Analysis   Check publisher's open access policy
ISSN 0167-9473
1872-7352
Publication date 2009-07-15
Year available 2008
Sub-type Article (original research)
DOI 10.1016/j.csda.2008.08.010
Volume 53
Issue 8
Start page 3033
End page 3046
Total pages 14
Place of publication Voorburg, Netherlands
Publisher Elsevier BV
Language eng
Formatted abstract A spatial process observed over a lattice or a set of irregular regions is usually modeled using a conditionally autoregressive (CAR) model. The neighborhoods within a CAR model are generally formed deterministically using the inter-distances or boundaries between the regions. An extension of CAR model is proposed in this article where the selection of the neighborhood depends on unknown parameter(s). This extension is called a Stochastic Neighborhood CAR (SNCAR) model. The resulting model shows flexibility in accurately estimating covariance structures for data generated from a variety of spatial covariance models. Specific examples are illustrated using data generated from some common spatial covariance functions as well as real data concerning radioactive contamination of the soil in Switzerland after the Chernobyl accident.
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ
Additional Notes Available online 15 August 2008.

Document type: Journal Article
Sub-type: Article (original research)
Collections: Institute for Social Science Research - Publications
ERA 2012 Admin Only
 
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