AIC_indices()

Function that returns the AIC of a list of models
In the case of a tweedie model (TweedGLM), it also returns the XI value to be used in crossvalidation if not fixed previously 
CovarExtract()

Function to extract covariates from different rasters 
CreateExtent()

Find area extent
Verify if this function is not in my spatial script 
Fig_split()

Find an equilibrated layout for a figure according to number of panels to include 
Map_predict()

Create Multilayer raster for predictions and uncertainty analysis 
ModelOrder()

Order fitted models 
ModelResults()

Study the outputs and predictions of a specific model 
Param_corr()

Function to identify covariates that are correlated in terms of Spearman's rank 
Prepare_covarStack()

Merge covariate rasters from different extents and projections into a multilayer Raster 
Prepare_dataset()

Prepare dataset to be included in the model selection procedure 
RefRasterize()

Create a RefRaster for regular grid dataset resampling 
Rm_WhiteMargins()

A function to crop white margins of a PNG image 
SDMSelect

SDMSelect: A package for crossvalidation model selection and species distribution mapping. 
best_distri()

A function to rank distributions (of same length) and statistically compare
them to the best one 
crossV_indices()

Function that return indices of quality of fit for a list of models with a
subsample of data used as validation sample in a crossvalidation procedure 
findBestModel()

Find best model 
fit_model()

Function to fit a model among all possible 
gplot_data

Transform raster as data.frame to be later used with ggplot
Modified from rasterVis::gplot 
is_ProjEqual()

Test if projections are equals 
meandiff_distri()

Mean difference between a distribution and a set of others
with or without weights 
model_select()

Characteristics of the model on which to produce outputs 
modelselect_opt()

Modelselect configuration file 
prec_data()

Find the most precise data of a vector 
predR()

Predictions in response and link scales 
spatialcor_dist()

Figure to see spatial autocorrelation that may allow to define the grid
size for gridded procedure 
test_opt()

Test internal modelopt 