Chapter Contents
Chapter Contents
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The NLP Procedure

Details


Criteria for Optimality

Optimization Algorithms

Finite-Difference Approximations of Derivatives

Hessian and CRP Jacobian Scaling

Testing the Gradient Specification

Termination Criteria

Active Set Methods

Feasible Starting Point

Line-Search Methods

Restricting the Step Length

Computational Problems

Covariance Matrix

Input and Output Data Sets

Printed Output

Computational Resources


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