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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>).
| Version: |
1.0.4 |
| Depends: |
R (≥ 3.4.0) |
| Imports: |
Rcpp, RcppParallel (≥ 0.11.2), MASS, ggplot2, scales |
| LinkingTo: |
Rcpp, RcppArmadillo, RcppParallel |
| Suggests: |
testthat (≥ 2.1.0), RColorBrewer, plot3D, pracma, spTimer, fields, maps, covr, V8 |
| Published: |
2023-11-21 |
| DOI: |
10.32614/CRAN.package.SpatMCA |
| Author: |
Wen-Ting Wang 
[aut, cre],
Hsin-Cheng Huang
[aut] |
| Maintainer: |
Wen-Ting Wang <egpivo at gmail.com> |
| BugReports: |
https://github.com/egpivo/SpatMCA/issues |
| License: |
GPL-3 |
| URL: |
https://github.com/egpivo/SpatMCA |
| NeedsCompilation: |
yes |
| SystemRequirements: |
GNU make |
| Materials: |
NEWS |
| CRAN checks: |
SpatMCA results |
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=SpatMCA
to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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