View source: R/4.f.calibration.R
calib_mdl | R Documentation |
This function will read an object of class ENMevaluation (See ?ENMeval::ENMevaluate for details) and calibrate the selected maxent models.
calib_mdl(
ENMeval.o,
sp.nm = "species",
a.calib,
occ = NULL,
use.ENMeval.bgpts = TRUE,
nbg = 10000,
format = "raster",
pred.args = c("outputformat=cloglog", "doclamp=true", "pictures=true"),
mSel = c("AvgAIC", "LowAIC", "OR", "AUC"),
wAICsum = 0.99,
dAICc = 2,
AUCmin = 0.7,
randomseed = FALSE,
responsecurves = TRUE,
arg1 = "noaddsamplestobackground",
arg2 = "noautofeature",
numCores = 1,
parallelTunning = TRUE
)
ENMeval.o |
Object of class ENMevaluation |
sp.nm |
Species name. Used to name the output folder |
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. |
occ |
Occurrence data. Argument 'p' of dismo::maxent. This can be a data.frame, matrix, SpatialPoints* object, or a vector. If p is a data.frame or matrix it represents a set of point locations; and it must have two columns with the first being the x-coordinate (longitude) and the second the y-coordinate (latitude). Coordinates can also be specified with a SpatialPoints* object If x is a data.frame, p should be a vector with a length equal to nrow(x) and contain 0 (background) and 1 (presence) values, to indicate which records (rows) in data.frame x are presence records, and which are background records |
use.ENMeval.bgpts |
Logical. Use background points from ENMeval or sample new ones? |
nbg |
Number of background points to use. These are sampled randomly from the cells that are not |
format |
Character. Output file type. Argument 'format' of raster::writeRaster |
pred.args |
Charater. Argument 'args' of dismo::maxent. Additional argument that can be passed to MaxEnt. See the MaxEnt help for more information. The R maxent function only uses the arguments relevant to model fitting. There is no point in using args='outputformat=raw' when *fitting* the model; but you can use arguments relevant for *prediction* when using the predict function. Some other arguments do not apply at all to the R implementation. An example is 'outputfiletype', because the 'predict' function has its own 'filename' argument for that. |
mSel |
Character vector. Which criteria to use when selecting model(s). Currently implemented: "AvgAIC", "LowAIC", "OR", "AUC" |
wAICsum |
Cumulative sum of top ranked models for which arguments will be created |
dAICc |
Maximum delta AICc of models to be selected. |
AUCmin |
Minimum AUC value to select models using EBPM criteria. |
randomseed |
logical. Args to be passed to dismo::maxent. See ?dismo::maxent and the MaxEnt help for more information. |
responsecurves |
logical. Args to be passed to dismo::maxent. See ?dismo::maxent and the MaxEnt help for more information. |
arg1 |
charater. Args to be passed to dismo::maxent. See ?dismo::maxent and the MaxEnt help for more information. |
arg2 |
charater. Args to be passed to dismo::maxent. See ?dismo::maxent and the MaxEnt help for more information. |
numCores |
Number of cores to use for parallelization. If set to 1, no paralellization is performed |
parallelTunning |
Should parallelize within species (parallelTunning=TRUE) or between species (parallelTunning=FALSE) |
A 'mcm' (calib.mdls, Maxent Calibrated Models). A list containing the models ('selected.mdls') used for model calibration, calibrated maxent models ('mxnt.mdls'), and arguments used for calibration ('pred.args').
mod_sel
, calib_mdl_b
, ENMevaluate_b
, ENMevaluate
,
maxent
, proj_mdl
, proj_mdl_b
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