Hooke-Jeeves Pattern Moves

A Nonlinear Estimation procedure, which at each iteration first defines a pattern of points by moving each parameter one by one so as to optimize the current loss function. The entire pattern of points is then shifted or moved to a new location; this new location is determined by extrapolating the line from the old base point in the m dimensional parameter space to the new base point. The step sizes in this process are constantly adjusted to "zero in" on the respective optimum. This method is usually quite effective, and should be tried if both the quasi-Newton and Simplex methods fail to produce reasonable estimates. See also Nonlinear Estimation Procedures - Function Minimization Algorithms.