Package: SpatMCA 1.0.4
Wen-Ting Wang
SpatMCA: Regularized Spatial Maximum Covariance Analysis
Provide regularized maximum covariance analysis incorporating smoothness, sparseness and orthogonality of couple patterns by using the alternating direction method of multipliers algorithm. The method can be applied to either regularly or irregularly spaced data, including 1D, 2D, and 3D (Wang and Huang, 2017 <doi:10.1002/env.2481>).
Authors:
SpatMCA_1.0.4.tar.gz
SpatMCA_1.0.4.tar.gz(r-4.5-noble)SpatMCA_1.0.4.tar.gz(r-4.4-noble)
SpatMCA_1.0.4.tgz(r-4.4-emscripten)SpatMCA_1.0.4.tgz(r-4.3-emscripten)
SpatMCA.pdf |SpatMCA.html✨
SpatMCA/json (API)
NEWS
| # Install 'SpatMCA' in R: |
| install.packages('SpatMCA', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/egpivo/spatmca/issues
Last updated 11 months agofrom:f728f564c5. Checks:OK: 1 NOTE: 1. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 17 2024 |
| R-4.5-linux-x86_64 | NOTE | Oct 17 2024 |
Exports:checkInputDatadetrendplot_cv_fieldplot_sequentiallyplot.spatmcasetCoresspatmcaspatmcacv_rcppspatmcacvall_rcpptpm2
Dependencies:clicolorspacefansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerRcppRcppArmadilloRcppParallelrlangscalestibbleutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Regularized Spatial Maximum Covariance Analysis | SpatMCA-package |
| Display the cross-validation results | plot.spatmca |
| Regularized spatial MCA | spatmca |
