Spatial prediction of N2O emissions in a Mooloolah pasture: posterior means and 95% credible intervals of parameters for three models
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The dataset is the product of a study which assessed the impact of three spatial correlation structures on spatial
predictions. Spatial predictions were calibrated using Bayesian model
averaging (BMA) based on replicated, irregular point-referenced data.
The data were measured in 17 chambers randomly placed across a 271 m2 field between October 2007 and September 2008 in Mooloolah, Queensland.
A Bayesian geostatistical model and a Bayesian spatial conditional autoregressive (CAR) model were used to investigate and accommodate spatial dependency, and to estimate the effects of environmental variables on N2O emissions across the study site.
The dataset shows the posterior means and 95% credible intervals (CI) of parameters for the CAR, EXP (spatial correlation described as the exponential decay function of the distance between pairs of points) and Independent (no spatial correlation structure) models.
The data were measured in 17 chambers randomly placed across a 271 m2 field between October 2007 and September 2008 in Mooloolah, Queensland.
A Bayesian geostatistical model and a Bayesian spatial conditional autoregressive (CAR) model were used to investigate and accommodate spatial dependency, and to estimate the effects of environmental variables on N2O emissions across the study site.
The dataset shows the posterior means and 95% credible intervals (CI) of parameters for the CAR, EXP (spatial correlation described as the exponential decay function of the distance between pairs of points) and Independent (no spatial correlation structure) models.
Location of data collection
kmlPolyCoords
152.963267,-26.765970
Publications
Huang, Xiaodong, Grace, Peter, Hu, Wenbiao, Rowlings, David, & Mengersen, Kerrie (2013) Spatial prediction of N2O emissions in pasture : a Bayesian model averaging analysis. PLoS ONE, 8(6).
http://eprints.qut.edu.au/67157/
Research areas
Geostatistics
Ecology
Interpolation
Spatial distribution
Environmental sciences
Geoinformatics
Environmental geography
Geography
Spatial autocorrelation
Soil science
Linear regression analysis
Nitrification
Soil chemistry
Bayes theorem
Global change ecology
Environmental chemistry
Spatial analysis
Cite this collection
Huang, XiaoDong; Grace, Peter; Hu, Wenbiao; Rowlings, David; Mengersen, Kerrie (2013): Posterior means and 95% credible intervals of parameters for three models for pasture. Table_2.xls. PLOS ONE.
Related information
Xiaodong Huang, Former QUT staff, Research collaborator
http://goo.gl/9RvXQ7
Access the data
Licence
Copyright
© 2013 Huang et al.
Dates of data collection
From 2007-10-01 to 2008-09-30
Connections
Contacts
Name: Distinguished Professor Kerrie Mengersen
Email: k.mengersen@qut.edu.au
Other
Date record created:
2014-07-02T14:00:24
Date record modified:
2019-07-04T09:33:55
Record status:
Published - Open Access