Solving the Nonlinear Least Square Problem: Application of a General Method.
Rept. for Oct 72-Dec 73,
AEROSPACE CORP EL SEGUNDO CALIF ENGINEERING SCIENCE OPERATIONS
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An algorithm for solving the general nonlinear least squares problem is developed. An estimate for the Hessian matrix is constructed as the sum of two matrices. The first matrix is the usual first-order estimate suggested by Gauss, while the second matrix is generated recursively using a rank-one formula. Test results indicate the method is superior to the standard Gauss method and compares favorably with other methods, especially for problems with nonzero residuals at the solution. Author
- Statistics and Probability