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.
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.
Related information
The work has been supported by the Cooperative Research Centre for Spatial Information
http://www.crcsi.com.au/
Access the data
Licence
Copyright
© 2013 Kang et al.
Dates of data collection
From 2013-01-01 to 2013-09-30
Connections
Contacts
Name: Distinguished Professor Kerrie Mengersen
Email: k.mengersen@qut.edu.au
Other
Date record created:
2014-07-02T09:46:19
Date record modified:
2019-07-04T09:13:47
Record status:
Published - Open Access