An application of novel zero-one inflated distributions with spatial dependence for the deforestation modeling

This paper considers statistical modeling of deforestation. Forest coverage ratio of grid-cell data was modeled by two covariates: human population density and relief energy. Conditional likelihood of the forest ratios given the covariates was decomposed by product of two likelihoods. The first one is due to trinomial logistic distributions on three classes: the ratios take zero, one or values between zero and one. The second one is due to a logistic-normal regression model for the ratios between zero and one. This model was applied to the real grid-cell data, and led remarkably interesting implications.