2015-06-11T21:30:56 n5751

The Impact of spatial scales and spatial smoothing on the outcome of Bayesian Spatial Model: summary of results for fitting four models at various spatial scales for various spatial patterns

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An investigation was completed to assess the impact of changes in spatial scale on model outcome for a set of spatial structures and to evaluate the performance of various Bayesian spatial smoothness priors for spatial dependence, namely an intrinsic Gaussian Markov random field (IGMRF), a second-order random walk (RW2D) on a lattice, and a Gaussian field with Matérn correlation function.

The dataset presents a summary of results for fitting four models at various spatial scales for various patterns.

Location of data collection

kmlPolyCoords
153.025013,-27.476409

Publications

Kang, Su Yun, McGree, James, & Mengersen, Kerrie (2013) The impact of spatial scales and spatial smoothing on the outcome of Bayesian spatial model. PLoS ONE, 18(10). http://eprints.qut.edu.au/65840/

Research areas

MATHEMATICAL SCIENCES
Random walk
Spatial distribution
Bayes theorem
Biological sciences
Disease ecology
Spatial and landscape ecology
Simulation and modelling
Biogeography
Markov models

Cite this collection

Kang, Su Yun; McGree, James; Mengersen, Kerrie (2013): Summary of results for fitting the four models at various spatial scales for various spatial patterns. Table_3.xls. PLOS ONE. 10.1371/journal.pone.0075957.t003

Related information

The work has been supported by the Cooperative Research Centre for Spatial Information http://www.crcsi.com.au/

Access the data

Licence


Creative Commons Attribution 4.0 (CC-BY)
http://creativecommons.org/licenses/by/4.0/

Copyright

© 2013 Kang et al.

Dates of data collection

From 2013-01-01 to 2013-09-30

Connections

Was collected by
Kerrie Mengersen  (Researcher)
Su Yun Kang   (Researcher)
James McGree  (Researcher)

Contacts

Other

Date record created:
2014-07-02T09:46:19
Date record modified:
2015-06-11T21:30:56
Record status:
Published - Open Access