Package: varycoef 0.3.6

Jakob A. Dambon
varycoef: Modeling Spatially Varying Coefficients
Implements a maximum likelihood estimation (MLE) method for estimation and prediction of Gaussian process-based spatially varying coefficient (SVC) models (Dambon et al. (2021a) <doi:10.1016/j.spasta.2020.100470>). Covariance tapering (Furrer et al. (2006) <doi:10.1198/106186006X132178>) can be applied such that the method scales to large data. Further, it implements a joint variable selection of the fixed and random effects (Dambon et al. (2021b) <doi:10.1080/13658816.2022.2097684>). The package and its capabilities are described in (Dambon et al. (2021c) <doi:10.48550/arXiv.2106.02364>).
Authors:
varycoef_0.3.6.tar.gz
varycoef_0.3.6.tar.gz(r-4.7-any)varycoef_0.3.6.tar.gz(r-4.6-any)
varycoef_0.3.6.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
varycoef/json (API)
| # Install 'varycoef' in R: |
| install.packages('varycoef', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/jakobdambon/varycoef/issues
Last updated from:858cdc5f76. Checks:4 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 191 | ||
| source / vignettes | OK | 255 | ||
| linux-release-x86_64 | OK | 185 | ||
| wasm-release | OK | 167 |
Exports:check_cov_lowercov_parGLS_cholinit_bounds_optimnlocssample_SVCdataSVC_mleSVC_mle_controlSVC_selectionSVC_selection_control
Dependencies:backportsBBmisccheckmateclicodetoolscpp11data.tabledotCall64farverfastmatchforeachggplot2glmnetgluegtableisobanditeratorslabelinglatticelhslifecycleMatrixmlrmlrMBOoptimParallelparallelMapParamHelperspbapplyR6RColorBrewerRcppRcppArmadilloRcppEigenrlangS7scalesshapesmoofspamstringisurvivalvctrsviridisLitewithrXML