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A Bayesian prediction using the skew Gaussian distribution
Authors:Hyoung-Moon Kim  Bani K. Mallick
Affiliation:

a Department of Computer and Mathematical Science, Texas A& M University, 6300 Ocean Drive, Corpus Christi, TX 78412, USA

b Texas A&M University, College Station, TX 77843-3143, USA

Abstract:
A model based on the skew Gaussian distribution is presented to handle skewed spatial data. It extends the results of popular Gaussian process models. Markov chain Monte Carlo techniques are used to generate samples from the posterior distributions of the parameters. Finally, this model is applied in the spatial prediction of weekly rainfall. Cross-validation shows that the predictive performance of our model compares favorably with several kriging variants.
Keywords:Kriging   Non-Gaussian characteristics   Markov chain Monte Carlo   Cross-validation
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