Comparing Bayesian spatial models: Goodness-of-smoothing criteria for assessing under- and over-smoothing.
Earl W DuncanKerrie L MengersenPublished in: PloS one (2020)
Some of the goodness-of-smoothing methods may be improved with modifications and better guidelines for their interpretation. However, these proposed goodness-of-smoothing methods offer researchers a solution to spatial model selection which is easy to implement. Moreover, they highlight the danger in relying on goodness-of-fit measures when comparing spatial models.
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