PGICA-package: Parallel Group ICA Algorithm

Description Details Author(s) References

Description

This package implements a Group ICA Alorithm which can run in parallel on clusters and multi-core personal computers. Unlike existing ICA algorithms, this parallel algorithm can analyze very big data. It can be used in many applications including signal processing and neuroimage data analysis.

Details

Package: PGICA
Type: Package
Version: 1.0
Date: 2014-11-12
License: GPL-2

The two main functions in this package are StVal and mica. mica is the main ICA function and StVal calculates initial values for mica.

Author(s)

Ani Eloyan, Shaojie Chen, Lei Huang, Huitong Qiu

Maintainer: <schen89@jhu.edu> Shaojie Chen

References

Ani Eloyan, Ciprian M. Crainiceanu and Brian S. Caffo: Likelihood Based Population Independent Component Analysis



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