Package: SpatialBSS 0.14-0

Klaus Nordhausen

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>.

Authors:Christoph Muehlmann [aut], Mika Sipil<e4> [aut], Klaus Nordhausen [aut, cre], Sara Taskinen [aut], Joni Virta [aut]

SpatialBSS_0.14-0.tar.gz
SpatialBSS_0.14-0.tar.gz(r-4.5-noble)SpatialBSS_0.14-0.tar.gz(r-4.4-noble)
SpatialBSS_0.14-0.tgz(r-4.4-emscripten)SpatialBSS_0.14-0.tgz(r-4.3-emscripten)
SpatialBSS.pdf |SpatialBSS.html✨
SpatialBSS/json (API)

# Install 'SpatialBSS' in R:
install.packages('SpatialBSS', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

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

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

13 exports 0.23 score 11 dependencies 1 dependents 349 downloads

Last updated 1 years agofrom:312ed85bad. Checks:OK: 1 WARNING: 1. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 13 2024
R-4.5-linux-x86_64WARNINGSep 13 2024

Exports:gen_glob_outlgen_loc_outllocal_covariance_matrixlocal_gss_covariance_matrixrobsbsssbsssbss_asympsbss_bootsnss_jdsnss_sdsnss_sjdspatial_kernel_matrixwhite_data

Dependencies:clueclusterDEoptimRdistancesJADElatticeRcppRcppArmadillorobustbasespSpatialNP

Spatial Blind Source Separation

Rendered fromSBSS.Rmdusingknitr::rmarkdownon Sep 13 2024.

Last update: 2022-11-16
Started: 2020-03-26

Readme and manuals

Help Manual

Help pageTopics
Blind Source Separation for Multivariate Spatial DataSpatialBSS-package
Coef Method for an Object of Class 'sbss'coef.sbss
Contamination with Global Outliersgen_glob_outl
Contamination with Local Outliersgen_loc_outl
Computation of Local Covariance Matriceslocal_covariance_matrix
Computation of Robust Local Covariance Matriceslocal_gss_covariance_matrix
Plot Method for an Object of Class 'sbss'plot.sbss
Predict Method for an Object of Class 'sbss'predict.sbss
Print Method for an Object of Class 'sbss'print.sbss
Robust Spatial Blind Source Separationrobsbss robsbss.default robsbss.sf robsbss.SpatialPointsDataFrame
Spatial Blind Source Separationsbss sbss.default sbss.sf sbss.SpatialPointsDataFrame
Asymptotic Test for the White Noise Dimension in a Spatial Blind Source Separation Modelsbss_asymp sbss_asymp.default sbss_asymp.sf sbss_asymp.SpatialPointsDataFrame
Different Bootstrap Tests for the White Noise Dimension in a Spatial Blind Source Separation Modelsbss_boot sbss_boot.default sbss_boot.sf sbss_boot.SpatialPointsDataFrame
Spatial Non-Stationary Source Separation Joint Diagonalizationsnss_jd snss_jd.default snss_jd.list snss_jd.sf snss_jd.SpatialPointsDataFrame
Spatial Non-Stationary Source Separation Simultaneous Diagonalizationsnss_sd snss_sd.default snss_sd.list snss_sd.sf snss_sd.SpatialPointsDataFrame
Spatial Non-Stationary Source Separation Spatial Joint Diagonalizationsnss_sjd snss_sjd.default snss_sjd.list snss_sjd.sf snss_sjd.SpatialPointsDataFrame
Computation of Spatial Kernel Matricesspatial_kernel_matrix
Different Approaches of Data Whiteningwhite_data