Guest lecture by Esa Ollila on November 11th

Academy Research Fellow Esa Ollila from Aalto University, will hold a presentation on FAST AND ROBUST BOOTSTRAP METHOD FOR TESTING HYPOTHESES IN THE ICA MODEL. The lecture will take place on Tuesday, 11th of November at 10:15 in the seminar room 469, Publicum 4th floor.

Abstract: Independent component analysis (ICA) is a widely used technique for extracting latent (unobserved) source signals from observed multidimensional measurements. In this paper we construct a fast and robust bootstrap (FRB) method for testing hypotheses on elements of the mixing matrix in the ICA model. The FRB method can be devised for estimators which are solutions to fixed-point (FP) equations.  We develop FRB test for the widely popular FastICA estimator. The developed test can be used in real-world ICA analysis of high-dimensional data sets  as it avoids the common obstacles of conventional bootstrap such as immense computational cost and lack of robustness. Moreover, instability and convergence problems of the FastICA algorithm when applied to bootstrap data are prevented. Simulations and examples illustrate the usefulness and validity of the developed test. Also, computation of the FastICA estimator using Newton-Raphson (NR) procedure is revisited.