Title: Testing the dimension of the non-Gaussian subspace in NGCA
Authors: Klaus Nordhausen - Vienna University of Technology (Austria) [presenting]
Hannu Oja - University of Turku (Finland)
David Tyler - Rutgers (United States)
Joni Virta - Aalto University (Finland)
Abstract: Dimension reduction is often a preliminary step in the analysis of large data sets. The so-called non-Gaussian component analysis (NGCA) searches for a projection onto the non-Gaussian part of the data, and it is then important to know the correct dimension of the non-Gaussian signal subspace. Different tests for the dimension based on the fourth order blind identification (FOBI) method are presented.