Data Mining Algorithms In R/Packages/optimsimplex/optimsimplex-package

Description
The goal of this package is to provide a building block for optimization algorithms based on a simplex. The 'optimsimplex package may be used in the following optimization methods:
 * the simplex method of Spendley et al.,
 * the method of Nelder and Mead,
 * the Box’s algorithm for constrained optimization,
 * the multi-dimensional search by Torczon,
 * etc ...

Features
The following is a list of features currently provided:
 * Manage various simplex initializations
 * initial simplex given by user,
 * initial simplex computed with a length and along the coordinate axes,
 * initial regular simplex computed with Spendley et al. formula,
 * initial simplex computed by a small perturbation around the initial guess point,
 * initial simplex computed from randomized bounds.
 * sort the vertices by increasing function values,
 * compute the standard deviation of the function values in the simplex,
 * compute the simplex gradient with forward or centered differences,
 * shrink the simplex toward the best vertex,
 * etc...

Authors
Author of Scilab optimsimplex module: Michael Baudin (INRIA - Digiteo) Author of R adaptation: Sebastien Bihorel (sb.pmlab@gmail.com)