Package: SpatMCA 1.0.7

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, 2018 <doi:10.1002/env.2481>).

Authors:Wen-Ting Wang [aut, cre], Hsin-Cheng Huang [aut]

SpatMCA_1.0.7.tar.gz
SpatMCA_1.0.7.tar.gz(r-4.7-arm64)SpatMCA_1.0.7.tar.gz(r-4.7-x86_64)SpatMCA_1.0.7.tar.gz(r-4.6-arm64)SpatMCA_1.0.7.tar.gz(r-4.6-x86_64)
SpatMCA_1.0.7.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
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

Pkgdown/docs site:https://egpivo.github.io

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

openblascppopenmp

1.00 score 4 scripts 158 downloads 1 exports 21 dependencies

Last updated from:ee9d5e17e1. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK157
linux-devel-x86_64OK178
source / vignettesOK189
linux-release-arm64OK166
linux-release-x86_64OK189
wasm-releaseOK131

Exports:spatmca

Dependencies:clicpp11farverggplot2gluegtableisobandlabelinglifecycleMASSR6RColorBrewerRcppRcppArmadilloRcppParallelrlangS7scalesvctrsviridisLitewithr