mop_b: Extrapolation risk analysis for a list of species

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

Extrapolation risk analysis for a list of species

Description

This function will compute the omission rate (OR) for each species' AICc Averaged Model from a 'mcmp.l' object, based on the selected threshold value.

Usage

mop_b(
  a.calib.l,
  a.proj.l,
  p = 0.1,
  q = 0.1,
  min.M.sz = 100,
  ref.scn = "current",
  format = "raster",
  numCores = 1
)

Arguments

a.calib.l	List of 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..
a.proj.l	A list of Raster* objects or data.frames where models will be projected. Argument 'x' of dismo::predict
p	Percent of values, sampled from calibration area, used as reference to calculate the MOP. Must be >0 and <=1.
q	Quantile. Proportion of closest points in M is to be compared with G to calculate the MOP. Must be >0 and <=1.
min.M.sz	Threshold value to be used to compute OR
ref.scn	Selected climatic scenario to compare with all others. Usually "ncurrent". any (row or col) is 0, it will draw the layout automatically.
format	Character. Output file type. Argument 'format' of raster::writeRaster
numCores	Number of cores to use for parallelization. If set to 1, no paralellization is performed

Value

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

See Also

mop

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