Last updated on 2026-02-05 03:50:21 CET.
| Package | ERROR | OK |
|---|---|---|
| CAST | 1 | 12 |
Current CRAN status: ERROR: 1, OK: 12
Version: 1.0.4
Check: re-building of vignette outputs
Result: ERROR
Error(s) in re-building vignettes:
...
--- re-building ‘cast01-CAST-intro.Rmd’ using rmarkdown
CAST package:CAST R Documentation
'_<08>c_<08>a_<08>r_<08>e_<08>t' _<08>A_<08>p_<08>p_<08>l_<08>i_<08>c_<08>a_<08>t_<08>i_<08>o_<08>n_<08>s _<08>f_<08>o_<08>r _<08>S_<08>p_<08>a_<08>t_<08>i_<08>a_<08>l-_<08>T_<08>e_<08>m_<08>p_<08>o_<08>r_<08>a_<08>l _<08>M_<08>o_<08>d_<08>e_<08>l_<08>s
_<08>D_<08>e_<08>s_<08>c_<08>r_<08>i_<08>p_<08>t_<08>i_<08>o_<08>n:
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-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 by analysing the similarity
between new data and training data. Methods are described in Meyer
et al. (2018); Meyer et al. (2019); Meyer and Pebesma (2021); Milà
et al. (2022); Meyer and Pebesma (2022); Linnenbrink et al.
(2023). The package is described in detail in Meyer et al. (2024).
_<08>D_<08>e_<08>t_<08>a_<08>i_<08>l_<08>s:
'caret' Applications for Spatio-Temporal models
_<08>A_<08>u_<08>t_<08>h_<08>o_<08>r(_<08>s):
Hanna Meyer, Carles Milà, Marvin Ludwig, Jan Linnenbrink, Fabian
Schumacher
_<08>R_<08>e_<08>f_<08>e_<08>r_<08>e_<08>n_<08>c_<08>e_<08>s:
• Meyer, H., Ludwig, L., Milà, C., Linnenbrink, J., Schumacher,
F. (2026): The CAST package for training and assessment of
spatial prediction models in R. In: Rocchini, D. (eds) R
Coding for Ecology. Use R!. Springer, Cham.
• Schumacher, F., Knoth, C., Ludwig, M., Meyer, H. (2025):
Estimation of local training data point densities to support
the assessment of spatial prediction uncertainty. Geosci.
Model Dev., 18, 10185–10202.
• Linnenbrink, J., Milà, C., Ludwig, M., and Meyer, H. (2024):
kNNDM: k-fold Nearest Neighbour Distance Matching
Cross-Validation for map accuracy estimation, Geosci. Model
Dev., 17, 5897–5912.
• Milà, C., Mateu, J., Pebesma, E., Meyer, H. (2022): Nearest
Neighbour Distance Matching Leave-One-Out Cross-Validation
for map validation. Methods in Ecology and Evolution 13,
1304– 1316.
• Meyer, H., Pebesma, E. (2022): Machine learning-based global
maps of ecological variables and the challenge of assessing
them. Nature Communications. 13.
• Meyer, H., Pebesma, E. (2021): Predicting into unknown space?
Estimating the area of applicability of spatial prediction
models. Methods in Ecology and Evolution. 12, 1620– 1633.
• Meyer, H., Reudenbach, C., Wöllauer, S., Nauss, T. (2019):
Importance of spatial predictor variable selection in machine
learning applications - Moving from data reproduction to
spatial prediction. Ecological Modelling. 411, 108815.
• Meyer, H., Reudenbach, C., Hengl, T., Katurji, M., Nauß, T.
(2018): Improving performance of spatio-temporal machine
learning models using forward feature selection and
target-oriented validation. Environmental Modelling &
Software 101: 1-9.
_<08>S_<08>e_<08>e _<08>A_<08>l_<08>s_<08>o:
Useful links:
• <https://github.com/HannaMeyer/CAST>
• <https://hannameyer.github.io/CAST/>
• Report bugs at <https://github.com/HannaMeyer/CAST/issues/>
trying URL 'https://geodata.ucdavis.edu/climate/worldclim/2_1/base/wc2.1_10m_bio.zip'
Content type 'application/zip' length 49869449 bytes (47.6 MB)
==================================================
downloaded 47.6 MB
trying URL 'https://geodata.ucdavis.edu/climate/worldclim/2_1/base/wc2.1_10m_elev.zip'
Content type 'application/zip' length 1332437 bytes (1.3 MB)
==================================================
downloaded 1.3 MB
[WARNING] Deprecated: --highlight-style. Use --syntax-highlighting instead.
--- finished re-building ‘cast01-CAST-intro.Rmd’
--- re-building ‘cast02-plotgeodist.Rmd’ using rmarkdown
trying URL 'https://geodata.ucdavis.edu/climate/worldclim/2_1/base/wc2.1_10m_bio.zip'
Content type 'application/zip' length 49869449 bytes (47.6 MB)
==================================================
downloaded 47.6 MB
[WARNING] Deprecated: --highlight-style. Use --syntax-highlighting instead.
--- finished re-building ‘cast02-plotgeodist.Rmd’
--- re-building ‘cast03-CV.Rmd’ using rmarkdown
Quitting from cast03-CV.Rmd:38-64 [read data]
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
<error/rlang_error>
Error:
! Cannot open "https://github.com/carlesmila/RF-spatial-proxies/raw/main/data/AP/PM25_train.gpkg"; The file doesn't seem to exist.
---
Backtrace:
▆
1. └─sf::read_sf("https://github.com/carlesmila/RF-spatial-proxies/raw/main/data/AP/PM25_train.gpkg")
2. ├─sf::st_read(...)
3. └─sf:::st_read.character(...)
4. └─sf:::CPL_read_ogr(...)
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Error: processing vignette 'cast03-CV.Rmd' failed with diagnostics:
Cannot open "https://github.com/carlesmila/RF-spatial-proxies/raw/main/data/AP/PM25_train.gpkg"; The file doesn't seem to exist.
--- failed re-building ‘cast03-CV.Rmd’
--- re-building ‘cast04-AOA-tutorial.Rmd’ using rmarkdown
[WARNING] Deprecated: --highlight-style. Use --syntax-highlighting instead.
--- finished re-building ‘cast04-AOA-tutorial.Rmd’
--- re-building ‘cast05-parallel.Rmd’ using rmarkdown
[WARNING] Deprecated: --highlight-style. Use --syntax-highlighting instead.
--- finished re-building ‘cast05-parallel.Rmd’
SUMMARY: processing the following file failed:
‘cast03-CV.Rmd’
Error: Vignette re-building failed.
Execution halted
Flavor: r-patched-linux-x86_64