mopaPredict0

model class object (e.g. "glm") or list of model class objects, e.g. as returned by function <code><a rd-options="mopa" href="/link/extractFromModel?package=mopa&version=1.0.1&to=mopa" data-mini-rdoc="mopa::extractFromModel">extractFromModel</a></code>.

models

RasterStack or list of RasterStacks of variables for projecting. If list, named lists are
recommended

newClim

Internal function for model projection into a RasterStack

internal

Tools for transferable species distribution modeling and pseudo-absence
data generation allowing the straightforward design of relatively complex experiments
with multiple factors affecting the uncertainty (variability) of SDM outputs
(pseudo-absence sample, climate projection, modeling algorithm, etc.), and the
quantification of the contribution of different factors to the final variability
following the method described in Deque el al. (2010) <doi:10.1007/s00382-011-1053-x>.
Multiple methods for pseudo-absence data generation can be applied, including the novel
Three-step method as described in Iturbide et al. (2015) <doi:10.1016/j.ecolmodel.2015.05.018>.
Additionally, a function for niche overlap calculation is provided, considering the metrics
described in Warren et al. (2008) <10.1111/j.1558-5646.2008.00482.x> and in
Pianka (1973) <10.1146/annurev.es.04.110173.000413>.

Maialen Iturbide

mopa

Species Distribution MOdeling with Pseudo-Absences

Joaquin Bedia

SantanderMetGroup http://meteo.unican.es

mopaPredict0 function

model class object (e.g. "glm") or list of model class objects, e.g. as returned by function <code><a rd-options='mopa' href='extractFromModel'>extractFromModel</a></code>.

mopaPredict0: Internal function for model prediction

Description

Usage

Arguments

Value

References

See Also