minor changes

DESCRIPTION

@@ -12,7 +12,7 @@ Authors@R: c(person("Hanna", "Meyer", email = "hanna.meyer@uni-muenster.de", rol
              person("Edzer", "Pebesma", role = c("ctb")))
 Author: Hanna Meyer [cre, aut], Carles Milà [aut], Marvin Ludwig [aut], Jan Linnenbrink [aut], Philipp Otto [ctb], Chris Reudenbach [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. CAST includes functions to improve spatial or spatial-temporal modelling tasks using 'caret'. It includes the newly suggested 'Nearest neighbor distance matching' cross-validation to estimate the performance of spatial prediction models and allows for spatial variable selection to selects suitable predictor variables in view to their contribution to the spatial model performance. CAST further includes functionality to estimate the (spatial) area of applicability of prediction models. Methods are described in Meyer et al. (2018) <doi:10.1016/j.envsoft.2017.12.001>; Meyer et al. (2019) <doi:10.1016/j.ecolmodel.2019.108815>; Meyer and Pebesma (2021) <doi:10.1111/2041-210X.13650>; Milà et al. (2022) <doi:10.1111/2041-210X.13851>; Meyer and Pebesma (2022) <doi:10.1038/s41467-022-29838-9>; Linnenbrink et al (2023) < doi:10.5194/egusphere-2023-1308>.
+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. CAST includes functions to improve spatial or spatial-temporal modelling tasks using 'caret'. It includes the newly suggested 'Nearest neighbor distance matching' cross-validation to estimate the performance of spatial prediction models and allows for spatial variable selection to selects suitable predictor variables in view to their contribution to the spatial model performance. CAST further includes functionality to estimate the (spatial) area of applicability of prediction models. Methods are described in Meyer et al. (2018) <doi:10.1016/j.envsoft.2017.12.001>; Meyer et al. (2019) <doi:10.1016/j.ecolmodel.2019.108815>; Meyer and Pebesma (2021) <doi:10.1111/2041-210X.13650>; Milà et al. (2022) <doi:10.1111/2041-210X.13851>; Meyer and Pebesma (2022) <doi:10.1038/s41467-022-29838-9>; Linnenbrink et al. (2023) <doi:10.5194/egusphere-2023-1308>.
 License: GPL (>= 2)
 URL: https://github.com/HannaMeyer/CAST,
     https://hannameyer.github.io/CAST/

NEWS.md

@@ -3,8 +3,8 @@
   * CAST functions now return classes with generic plotting and printing
   * new dataset for examples, tutorials and testing: data(splotdata)
 * modifications:
-  * calibrate_aoa is now DItoErrormetric and return a model (see function documentation)
-  * plot_geodist turned into geodist function with plot()
+  * calibrate_aoa is now DItoErrormetric and returns a model (see function documentation)
+  * plot_geodist is now geodist. The result can be visualized with plot()
   * plot_ffs is now plot(ffs)
 * bug fix:
   * fix issue #65 (threshold)