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AIC_indices()
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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 cross-validation if not fixed previously |
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CovarExtract()
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Function to extract covariates from different rasters |
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CreateExtent()
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Find area extent
Verify if this function is not in my spatial script |
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Fig_split()
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Find an equilibrated layout for a figure according to number of panels to include |
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Map_predict()
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Create Multilayer raster for predictions and uncertainty analysis |
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ModelOrder()
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Order fitted models |
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ModelResults()
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Study the outputs and predictions of a specific model |
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Param_corr()
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Function to identify covariates that are correlated in terms of Spearman's rank |
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Prepare_covarStack()
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Merge covariate rasters from different extents and projections into a multi-layer Raster |
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Prepare_dataset()
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Prepare dataset to be included in the model selection procedure |
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RefRasterize()
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Create a RefRaster for regular grid dataset resampling |
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Rm_WhiteMargins()
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A function to crop white margins of a PNG image |
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SDMSelect
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SDMSelect: A package for cross-validation model selection and species distribution mapping. |
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best_distri()
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A function to rank distributions (of same length) and statistically compare
them to the best one |
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crossV_indices()
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Function that return indices of quality of fit for a list of models with a
sub-sample of data used as validation sample in a cross-validation procedure |
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findBestModel()
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Find best model |
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fit_model()
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Function to fit a model among all possible |
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gplot_data
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Transform raster as data.frame to be later used with ggplot
Modified from rasterVis::gplot |
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is_ProjEqual()
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Test if projections are equals |
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meandiff_distri()
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Mean difference between a distribution and a set of others
with or without weights |
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model_select()
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Characteristics of the model on which to produce outputs |
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modelselect_opt()
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Modelselect configuration file |
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prec_data()
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Find the most precise data of a vector |
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predR()
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Predictions in response and link scales |
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spatialcor_dist()
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Figure to see spatial autocorrelation that may allow to define the grid
size for gridded procedure |
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test_opt()
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Test internal modelopt |