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Overview of Newton-Raphson Algorithm for Nonlinear Least Squares Estimation

This document provides an in-depth overview of the Newton-Raphson (NR) algorithm as applied to nonlinear least squares (NLS) estimation. It discusses the general algorithm, compares it with the Gauss-Newton (GN) algorithm, and presents examples including a parameter and an exogenous variable. Additionally, it explores extensions of basic estimation algorithms to more general cases and outlines the development of GN NLS procedures. Finally, it addresses nonlinear macro-consumption models and emphasizes essential post-estimation analysis techniques.

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Overview of Newton-Raphson Algorithm for Nonlinear Least Squares Estimation

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  1. AAE637 Topics for Jan. 31, 2008 • Overview of Newton-Raphson (NR) Algorithm for NLS Estimation • General Algorithm • Comparison with GN algorithm • 1 Param., 2 Exog. Variable Example • Extension of Our Basic Estimation Algorithms to More General Case • Development of GN NLS Procedure • Nonlinear Macro-Consumption • Post-Estimation Analysis

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