Comparison of recurrent methods of parameter estimation in macromodeling problems

The paper suggests new modifications of Gauss and Gramm-Schmidt methods for recurrent parameter estimation of sequentially complicated structures of regression models when modeling from data. The results of run time comparison of these algorithms with a recurrent algorithm based on the known bordering method are presented.