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ModelMap: Modeling and Map Production using Random Forest and Related Stochastic Models

Creates sophisticated models of training data and validates the models with an independent test set, cross validation, or Out Of Bag (OOB) predictions on the training data. Create graphs and tables of the model validation results. Applies these models to GIS .img files of predictors to create detailed prediction surfaces. Handles large predictor files for map making, by reading in the .img files in chunks, and output to the .txt file the prediction for each data chunk, before reading the next chunk of data.

Version: 3.4.0.4
Depends: R (≥ 2.13.0), randomForest, raster
Imports: graphics, grDevices, stats, utils, mgcv, corrplot, fields, HandTill2001, PresenceAbsence
Suggests: party, quantregForest
Published: 2023-04-24
Author: Elizabeth Freeman, Tracey Frescino
Maintainer: Elizabeth Freeman <elizabeth.a.freeman at usda.gov>
License: Unlimited
Copyright: see file COPYRIGHTS
NeedsCompilation: no
Citation: ModelMap citation info
Materials: ChangeLog
In views: Spatial
CRAN checks: ModelMap results

Documentation:

Reference manual: ModelMap.pdf
Vignettes: Exploratory Data Analysis with the ModelMap package
ModelMap: an R package for Model Creation and Map Production
Pick your flavor of Random Forest

Downloads:

Package source: ModelMap_3.4.0.4.tar.gz
Windows binaries: r-devel: ModelMap_3.4.0.4.zip, r-release: ModelMap_3.4.0.4.zip, r-oldrel: ModelMap_3.4.0.4.zip
macOS binaries: r-release (arm64): ModelMap_3.4.0.4.tgz, r-oldrel (arm64): ModelMap_3.4.0.4.tgz, r-release (x86_64): ModelMap_3.4.0.4.tgz, r-oldrel (x86_64): ModelMap_3.4.0.4.tgz
Old sources: ModelMap archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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