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  • A set of functions for covariate selection and model specifications with cross-validation and forward model selection. It selects GAM, GLM models using a multiple k-fold cross-validation and map species distribution while accounting for model uncertainties. Multiple families are possible and compared all together using RMSE or AUC as a result of cross-validation procedure. Covariates correlation may be tested. The model selection procedure will test different combinations of covariates with LM, GLM, GLM natural splines and GAM models, with different distributions (Gaussian, Gamma, Log-Normal, Tweedie; Binomial) and with different maximum degrees of freedom for GLM with polynoms or natural splines. Calculations are parallelized when possible. Outputs are numerous, allowing for summary of the model selection and the comparison of the different models all together. The final model selected is used to map species distribution along with maps of uncertainty.