Spatial prediction of N2O emissions in a Mooloolah pasture: posterior means and 95% credible intervals of parameters for three models

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.