Function to create an ensemble of spartial effects from multiple models
Source:R/ensemble.R
ensemble_spartial.Rd
Similar to the ensemble()
function, this function creates an
ensemble of partial responses of provided distribution models fitted with
the ibis.iSDM-package
. Through the layer
parameter it can be
specified which part of the partial prediction should be averaged in an
ensemble (if given). This can be for instance the mean prediction and/or
the standard deviation sd. Ensemble partial is also being called if more
than one input DistributionModel
object is provided to partial
.
By default the ensemble of partial responses is created as average across all models with the uncertainty being the standard deviation of responses.
Usage
ensemble_spartial(
...,
x.var,
method = "mean",
layer = "mean",
newdata = NULL,
min.value = NULL,
normalize = TRUE
)
# S4 method for class 'ANY'
ensemble_spartial(
...,
x.var,
method = "mean",
layer = "mean",
newdata = NULL,
min.value = NULL,
normalize = TRUE
)
Arguments
- ...
Provided
DistributionModel
objects from which partial responses can be called. In the future provided data.frames might be supported as well.- x.var
A
character
of the variable from which an ensemble is to be created.- method
Approach on how the ensemble is to be created. See details for options (Default:
'mean'
).- layer
A
character
of the layer to be taken from each prediction (Default:'mean'
). If set toNULL
ignore any of the layer names in ensembles ofSpatRaster
objects.- newdata
A optional
data.frame
orSpatRaster
object supplied to the model (DefaultLNULL
). This object needs to have identical names as the original predictors.- min.value
A optional
numeric
stating a minimum value that needs to be surpassed in each layer before calculating and ensemble (Default:NULL
).- normalize
logical
on whether the inputs of the ensemble should be normalized to a scale of 0-1 (Default:TRUE
).
Value
A SpatRaster object with the combined partial effects of the supplied models.
Details
Possible options for creating an ensemble includes:
'mean'
- Calculates the mean of several predictions.'median'
- Calculates the median of several predictions.
Note
If a list is supplied, then it is assumed that each entry in the list
is a fitted DistributionModel
object. Take care not to create an ensemble
of models constructed with different link functions, e.g. logistic vs log.
By default the response functions of each model are normalized.