  Dimension reduction is a common strategy in multivariate data analysis which
seeks a subspace which contains all interesting features needed for the
subsequent analysis. Non-Gaussian component analysis attempts for this purpose
to divide the data into a non-Gaussian part, the signal, and a Gaussian part,
the noise. We will show that the simultaneous use of two scatter functionals
can be used for this purpose and suggest a bootstrap test to test the dimension
of the non-Gaussian subspace. Sequential application of the test can then for
example be used to estimate the signal dimension.
