
Summary: A new algorithm is given for calculating the least squares estimates and robust estimates, etc., of parameters of nonlinear regression models. Many examples show that the present algorithm is useful and effective.
General nonlinear regression, Point estimation, new algorithm, Probabilistic methods, stochastic differential equations, Robustness and adaptive procedures (parametric inference), robust estimates, least squares estimates
General nonlinear regression, Point estimation, new algorithm, Probabilistic methods, stochastic differential equations, Robustness and adaptive procedures (parametric inference), robust estimates, least squares estimates
