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SpatialBSS (version 0.16-0)

Blind Source Separation for Multivariate Spatial Data

Description

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) .

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Version

Install

install.packages('SpatialBSS')

Monthly Downloads

215

Version

0.16-0

License

GPL (>= 2)

Maintainer

Klaus Nordhausen

Last Published

March 27th, 2025

Functions in SpatialBSS (0.16-0)

plot.sbss

Plot Method for an Object of Class 'sbss'
predict.sbss

Predict Method for an Object of Class 'sbss'
gen_glob_outl

Contamination with Global Outliers
SpatialBSS-package

Blind Source Separation for Multivariate Spatial Data
gen_loc_outl

Contamination with Local Outliers
local_gss_covariance_matrix

Computation of Robust Local Covariance Matrices
coef.sbss

Coef Method for an Object of Class 'sbss'
print.sbss

Print Method for an Object of Class 'sbss'
robsbss

Robust Spatial Blind Source Separation
sbss

Spatial Blind Source Separation
veneto_weather

Weekly Aggregated Climate and Meteorological Data in Veneto, Italy
spatial_kernel_matrix

Computation of Spatial Kernel Matrices
white_data

Different Approaches of Data Whitening
sbss_asymp

Asymptotic Test for the White Noise Dimension in a Spatial Blind Source Separation Model
sbss_boot

Different Bootstrap Tests for the White Noise Dimension in a Spatial Blind Source Separation Model
snss_jd

Spatial Non-Stationary Source Separation Joint Diagonalization
snss_sd

Spatial Non-Stationary Source Separation Simultaneous Diagonalization
snss_sjd

Spatial Non-Stationary Source Separation Spatial Joint Diagonalization
local_covariance_matrix

Computation of Local Covariance Matrices