ON THE NONPARAMETRIC CLASSIFICATION AND REGRESSION METHODS FOR MULTIVARIATE EAS DATA-ANALYSIS

Based on a special data analysis methodology developed for non-direct multivariate experiments, we present the expected accuracies of the KA SCADE experiment on the elemental composition and primary energy estim ation. The calculations were carried out with CORSIKA simulations usin g the ANI applied package routines. The detector responce also was sim ulated. The Neural Networks classification, the Bayesian Decision Maki ng and the Nonparametric Regression approaches are used and compared.