optextras (2019-12.4)

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Tools to Support Optimization Possibly with Bounds and Masks.


Tools to assist in safely applying user generated objective and derivative function to optimization programs. These are primarily function minimization methods with at most bounds and masks on the parameters. Provides a way to check the basic computation of objective functions that the user provides, along with proposed gradient and Hessian functions, as well as to wrap such functions to avoid failures when inadmissible parameters are provided. Check bounds and masks. Check scaling or optimality conditions. Perform an axial search to seek lower points on the objective function surface. Includes forward, central and backward gradient approximation codes.

Maintainer: John C. Nash
Author(s): John C Nash [aut, cre]

License: GPL-2

Uses: numDeriv
Reverse depends: Rvmmin

Released about 1 month ago.

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