predict_bart: Make Predictions Using a BART Model
In glossa: User-Friendly 'shiny' App for Bayesian Species Distribution Models
View source: R/bart_functions.R
predict_bart R Documentation
Make Predictions Using a BART Model
Description
This function makes predictions using a Bayesian Additive Regression Trees (BART) model
on a stack of environmental covariates ('SpatRaster').
Usage
predict_bart(bart_model, layers, cutoff = NULL)
Arguments
bart_model
A BART model object obtained from fitting BART using the 'dbarts' package.
layers
A SpatRaster object containing environmental covariates for prediction.
cutoff
An optional numeric cutoff value for determining potential presences. If NULL, potential presences and absences will not be computed.
Value
A SpatRaster containing the mean, median, standard deviation, and quantiles
of the posterior predictive distribution, as well as a potential presences layer if cutoff is provided.
glossa documentation built on June 8, 2025, 1:20 p.m.
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View source: R/bart_functions.R
| predict_bart | R Documentation |
Make Predictions Using a BART Model
Description
This function makes predictions using a Bayesian Additive Regression Trees (BART) model on a stack of environmental covariates ('SpatRaster').
Usage
predict_bart(bart_model, layers, cutoff = NULL)
Arguments
bart_model |
A BART model object obtained from fitting BART using the 'dbarts' package. |
layers |
A SpatRaster object containing environmental covariates for prediction. |
cutoff |
An optional numeric cutoff value for determining potential presences. If NULL, potential presences and absences will not be computed. |
Value
A SpatRaster containing the mean, median, standard deviation, and quantiles of the posterior predictive distribution, as well as a potential presences layer if cutoff is provided.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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