Abstract
A procedure for solving nonlinear estimation problems, designed with the special case of fitting nonlinear regression relationships in mind, will be described. It is an analytic search technique using two classic search procedures in parametric combination. This enables one at each iteration to concentrate attention on minimizing sumof-squares deviation with respect to the single combination parameter. Using projected gradients, the procedure may also be applied to linearly constrained problems.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
