The dogleg method is an iterative optimization technique used to solve nonlinear least squares problems by balancing the trade-off between a steepest descent direction and a trust region constraint. This approach utilizes a combination of a Cauchy point and a Newton step to navigate through the solution space while maintaining feasibility within the trust region. It effectively integrates elements of both local optimization and constrained optimization, making it particularly useful in scenarios where traditional methods may struggle.
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