For symmetric problems, at least one of the subproblems is a

nonlinear least squares problem, e.

If the residuals of N meet normality, it would be feasible to use the

nonlinear least square regression or other standard fitting methods, like the least RSS.

Solution of

nonlinear least squares problems by Levenberg-Marquardt type methods.

2) Apply the

Nonlinear Least Square (NLS) method to estimate the parameters of the specified function.

Two different nonlinear optimization algorithms were utilized for comparison:

nonlinear least squares (NLS) and simplex search (SS).

These models include OLS on log (positive) expenditures,

nonlinear least squares, and GLM with a log-link function; all are multiplicative.

In addition, the extension of these methods to

nonlinear least squares and the incorporation of a trust region strategy with tensor methods are new contributions.

In the first step, for a particular creep stress, Eq 12 is used to fit the corresponding experimental creep curve using a procedure providing a

nonlinear least squares fit.

A

nonlinear least squares method is used to estimate the system of equations (6) and (10).

This paper is concerned with the development, numerical implementation, and testing of an algorithm for solving constrained

nonlinear least squares problems.

The key to deriving a full Newton algorithm for solving a

nonlinear least squares problem is to build a quadratic model for the squared norm of the residual at the current point ac and minimize that at each step; see, for instance, [3].

TENSOLVE: A software package for solving systems of nonlinear equations and

nonlinear least squares problems using tensor methods.