THE USE OF MONTE-CARLO METHODS IN FACTOR-ANALYSIS

Monte Carlo techniques are introduced in target transformation factor analysis (TTFA), in combination with the concept of the principal fact or model, in order to account for local variances in the data set and to estimate the uncertainties in the obtained source profiles. The new method is validated using several types of artificial data sets. It w as found that application of the Monte Carlo method leads to a signifi cant improvement of the accuracy of the derived source profiles in com parison with standard TTFA. From the introduction of (known) error sou rces to the artificial data sets it was found that the source-profile reproduction quality is optimal if the magnitudes of the Monte Carlo v ariations are chosen equal to the magnitudes of the introduced errors.