c(person("Hanna", "Meyer", email = "hanna.meyer@uni-muenster.de", role = c("cre", "aut")),
person("Carles", "Milà", role = c("aut")),
person("Marvin", "Ludwig", role = c("aut")),
person("Chris", "Reudenbach", role = c("ctb")),
person("Thomas", "Nauss", role = c("ctb")),
person("Edzer", "Pebesma", role = c("ctb")))
Hanna Meyer [cre, aut],
Carles Milà [aut],
Marvin Ludwig [aut],
Chris Reudenbach [ctb],
Thomas Nauss [ctb],
Edzer Pebesma [ctb]
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>.
doParallel, randomForest, lubridate, raster, sp, knitr,
mapview, rmarkdown, sf, scales, parallel, latticeExtra,
virtualspecies, gridExtra, viridis, rgeos, stars, scam, terra,
rnaturalearth, rgdal

The Cochran-Armitage trend test can be applied to a two by k contingency table. The test statistic (Z) and p-value will be reported. A linear trend in the frequencies will be calculated, because the weights (0,1,2) will be used by default.

This function conducts the Cochran-Armitage trend test to a 2 by k contingency table. It will report the test statistic (Z) and p-value.A linear trend in the frequencies will be calculated, because the weights (0,1,2) will be used by default.