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PearsonICA
View on CRAN: Click
here
Download and install PearsonICA package within the R console
Install from CRAN:
install.packages("PearsonICA")
Install from Github:
library("remotes")
install_github("cran/PearsonICA")
Install by package version:
library("remotes")
install_version("PearsonICA", "1.2-5")
Attach the package and use:
library("PearsonICA")
Maintained by
Juha Karvanen
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2006-06-29
Latest Update: 2022-02-21
Description:
The Pearson-ICA algorithm is a mutual information-based
method for blind separation of statistically independent source
signals. It has been shown that the minimization of mutual
information leads to iterative use of score functions, i.e.
derivatives of log densities. The Pearson system allows
adaptive modeling of score functions. The flexibility of the
Pearson system makes it possible to model a wide range of
source distributions including asymmetric distributions. The
algorithm is designed especially for problems with asymmetric
sources but it works for symmetric sources as well.
How to cite:
Juha Karvanen (2006). PearsonICA: Independent Component Analysis using Score Functions from the Pearson System. R package version 1.2-5, https://cran.r-project.org/web/packages/PearsonICA. Accessed 09 Jun. 2025.
Previous versions and publish date:
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imports, suggests or enhances
Complete documentation for PearsonICA
Functions, R codes and Examples using
the PearsonICA R package
Some associated functions: PearsonICA . PearsonICAdemo .
Some associated R codes: PearsonICA.R . Full PearsonICA package functions and examples
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