Details

Autor(en) / Beteiligte

• Miettinen, Jari
• Nordhausen, Klaus
• Taskinen, Sara

Titel

Blind Source Separation Based on Joint Diagonalization in R : The Packages JADE and BSSasymp

Ist Teil von

• Journal of statistical software, 2017, Vol.76 (2), p.1-31

Ort / Verlag

Foundation for Open Access Statistics

Erscheinungsjahr

2017

Link zum Volltext

Quelle

EZB Electronic Journals Library

Beschreibungen/Notizen

• Blind source separation (BSS) is a well-known signal processing tool which is used to solve practical data analysis problems in various fields of science. In BSS, we assume that the observed data consists of linear mixtures of latent variables. The mixing system and the distributions of the latent variables are unknown. The aim is to find an estimate of an unmixing matrix which then transforms the observed data back to latent sources. In this paper we present the R packages JADE and BSSasymp. The package JADE offers several BSS methods which are based on joint diagonalization. Package BSSasymp contains functions for computing the asymptotic covariance matrices as well as their data-based estimates for most of the BSS estimators included in package JADE. Several simulated and real datasets are used to illustrate the functions in these two packages.