Package: CAST
Type: Package
Title: 'caret' Applications for Spatial-Temporal Models
Version: 0.5.1
Authors@R: c(person("Hanna", "Meyer", email = "hanna.meyer@uni-muenster.de", role = c("cre", "aut")),
             person("Chris", "Reudenbach", role = c("ctb")),
             person("Marvin", "Ludwig", role = c("ctb")),
             person("Thomas", "Nauss", role = c("ctb")),
             person("Edzer", "Pebesma", role = c("ctb")))
Author: Hanna Meyer [cre, aut],
  Chris Reudenbach [ctb],
  Marvin Ludwig [ctb],
  Thomas Nauss [ctb],
  Edzer Pebesma [ctb]
Maintainer: Hanna Meyer <hanna.meyer@uni-muenster.de>
Description: Supporting functionality to run 'caret' with spatial or spatial-temporal data. 'caret' is a frequently used package for model training and prediction using machine learning. This package includes functions to improve spatial-temporal modelling tasks using 'caret'. It prepares data for Leave-Location-Out and Leave-Time-Out cross-validation which are target-oriented validation strategies for spatial-temporal models. To decrease overfitting and improve model performances, the package implements a forward feature selection that selects suitable predictor variables in view to their contribution to the target-oriented performance. CAST further includes functionality to estimate the (spatial) area of applicability of prediction models by analysing the similarity between new data and training data.
License: GPL (>= 2)
URL: https://github.com/HannaMeyer/CAST
Encoding: UTF-8
LazyData: false
Depends: R (>= 3.5.0)
Imports: caret, stats, utils, ggplot2, graphics, reshape, FNN, plyr,
        zoo, methods, grDevices, data.table, lattice
Suggests: doParallel, randomForest, lubridate, raster, sp, knitr,
        mapview, rmarkdown, sf, scales, parallel, latticeExtra,
        virtualspecies, gridExtra, viridis, rgeos, stars, scam
RoxygenNote: 7.1.0
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-04-07 07:55:11 UTC; hanna
Repository: CRAN
Date/Publication: 2021-04-07 13:20:17 UTC
Built: R 4.0.5; ; 2022-03-18 05:38:35 UTC; windows
