1 / 1

Introduction to Nonlinear Least Squares: Quadratic Functions and NLLS Algorithms

This document explores nonlinear least squares (NLLS) beginning with an introduction to the technique, exemplified by a quadratic function. It provides an overview of the Gauss-Newton (GN) algorithms used in NLLS, including case studies on single and multiple parameters. The properties of NLLS estimators are discussed, alongside a brief overview of the Newton-Raphson (NR) algorithm. This serves as a foundational guide for understanding and applying nonlinear regression methodologies.

angeni
Télécharger la présentation

Introduction to Nonlinear Least Squares: Quadratic Functions and NLLS Algorithms

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. AAE637 Topics for March 22, 2007 • Introduction to Nonlinear Least Squares • Example of Quadratic Function • Overview of NLLS GN Algorithms • Single Parameter • Quadratic Function Example • Extension to Multiple Parameters • Properties of NLLS estimators • Brief Overview of NLLS NR Algorithm • Single Parameter

More Related