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SpatialBSS: Blind Source Separation for Multivariate Spatial Data

Blind source separation for multivariate spatial data based on simultaneous/joint diagonalization of (robust) local covariance matrices. This package is an implementation of the methods described in Bachoc, Genton, Nordhausen, Ruiz-Gazen and Virta (2020) <doi:10.1093/biomet/asz079>.

Version: 0.14-0
Imports: Rcpp (≥ 1.0.2), JADE, sp, stats, SpatialNP, distances, robustbase
LinkingTo: Rcpp, RcppArmadillo
Suggests: sf, knitr, rmarkdown, markdown, gstat
Published: 2023-07-20
Author: Christoph Muehlmann ORCID iD [aut], Mika Sipil<e4> ORCID iD [aut], Klaus Nordhausen ORCID iD [aut, cre], Sara Taskinen ORCID iD [aut], Joni Virta ORCID iD [aut]
Maintainer: Klaus Nordhausen <klausnordhausenR at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
CRAN checks: SpatialBSS results

Documentation:

Reference manual: SpatialBSS.pdf
Vignettes: SBSS

Downloads:

Package source: SpatialBSS_0.14-0.tar.gz
Windows binaries: r-devel: SpatialBSS_0.14-0.zip, r-release: SpatialBSS_0.14-0.zip, r-oldrel: SpatialBSS_0.14-0.zip
macOS binaries: r-release (arm64): SpatialBSS_0.14-0.tgz, r-oldrel (arm64): SpatialBSS_0.14-0.tgz, r-release (x86_64): SpatialBSS_0.14-0.tgz, r-oldrel (x86_64): SpatialBSS_0.14-0.tgz
Old sources: SpatialBSS archive

Reverse dependencies:

Reverse imports: BSSoverSpace

Linking:

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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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