Temporal Ecological Niche Models
Helper function to obtain layer name from a raster layer
Function to obtain environmental background organized by date
Helper function to randomly select cell IDs for generating environment...
Function to thin occurrence data Cleans up duplicated longitude and la...
Function to thin longitude and latitude data
Function to find strong correlations within environmental predictors
Function to compute the covariance matrix of an ellipsoid niche model.
Compute omission rate and statistical metrics for ellipsoid models.
ellipsoid_projection: function to project an ellipsoid model
ellipsoid_selection: Performs models selection for ellipsoid models
Extract environmental data by date
inEllipsoid: Determine if a point is inside or outside an ellipsoid
Function to plot ellipsoid models in E-space
Predict the potential distribution of species based on environmental c...
Partial ROC calculation for Niche Models
Function to create a Species Temporal Data object (STD object).
S3 classes to organize data and results of tenm objects
S3 classes to organize data and results of tenm objects
S3 classes to organize data and results of tenm objects
S3 classes to organize data and results of tenm objects
Temporal data.frame to Samples With Data format
Function to find the best n-dimensional ellipsoid model
Implements methods and functions to calibrate time-specific niche models (multi-temporal calibration), letting users execute a strict calibration and selection process of niche models based on ellipsoids, as well as functions to project the potential distribution in the present and in global change scenarios.The 'tenm' package has functions to recover information that may be lost or overlooked while applying a data curation protocol. This curation involves preserving occurrences that may appear spatially redundant (occurring in the same pixel) but originate from different time periods. A novel aspect of this package is that it might reconstruct the fundamental niche more accurately than mono-calibrated approaches. The theoretical background of the package can be found in Peterson et al. (2011)<doi:10.5860/CHOICE.49-6266>.