get_or_ensemble: Compute Omission Rate for a species' ensembled model

In HemingNM/ENMwizard: Advanced Techniques for Ecological Niche Modeling Made Easy

Compute Omission Rate for a species' ensembled model

Description

This function will compute the omission rate (OR) for a species' ensembled model from a 'mcmp' object, based on the selected threshold value.

Usage

get_or_ensemble(
  mcm,
  a.calib,
  ORt = seq(0, 0.2, 0.05),
  userArgs = NULL,
  categoricals,
  sp.nm = "species"
)

Arguments

mcm	Objects returned by "calib_mdl", containing calibrated models.
a.calib	Predictors (cropped environmental variables) for model tuning. Used in model calibration. Argument 'x' of dismo::maxent. Raster* object or SpatialGridDataFrame, containing grids with predictor variables. These will be used to extract values from for the point locations. Can also be a data.frame, in which case each column should be a predictor variable and each row a presence or background record.
ORt	Threshold value to be used to compute OR
userArgs	character vector; use this to pass other arguments (e.g., prevalence) to the 'maxent' call. Note that not all options are functional or relevant.
categoricals	Vector indicating which (if any) of the input environmental layers are categorical.
sp.nm	Species name. Used to name the output folder

Value

Data frame with average and variance of OR values across partition groups of data

See Also

get_or_ensemble_b, get_tsa, get_cont_permimport, get_fpa, get_cont_permimport_b, get_fpa_b, get_tsa_b

HemingNM/ENMwizard documentation built on Jan. 4, 2024, 3:24 p.m.