Nonlinear Least Squares Problem without Constraints

The nonlinear least squares problem without constraints can be described as follows:



F(x) : RnRm is a twice differentiable function in Rn.

Solving a nonlinear least squares problem means searching for the best approximation to the vector y with the model function fi(x) and nonlinear variables x. The best approximation means that the sum of squares of residuals yi - fi(x) is the minimum.

See usage examples in Fortran and C in the examples\solverf\source and examples\solverc\source folders of your Intel MKL directory, respectively. Specifically, see ex_nlsqp_f.f and ex_nlsqp_c.c.

RCI TR Routines

Routine Name



Initializes the solver.


Checks correctness of the input parameters.


Solves a nonlinear least squares problem using the Trust-Region algorithm.


Retrieves the number of iterations, stop criterion, initial residual, and final residual.


Releases allocated data.

For more complete information about compiler optimizations, see our Optimization Notice.