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    Dealing with high pareto k values

    I'm using the new R package 'UBMS' which uses STAN within a Bayesian framework to model occupancy and species distribution. My current 'best' model based on LOOIC values is the following; m.final <- stan_occuRN(~v.dens ~v.type + NDVI + lat+ village + mainroad + (1|site), data=UFO3, chains=3...