# n1qn1 v6.0.1-3

0

0th

Percentile

## Port of the 'Scilab' 'n1qn1' and 'qnbd' Modules for (Un)constrained BFGS Optimization

Provides 'Scilab' 'n1qn1', or Quasi-Newton BFGS "qn" without constraints and 'qnbd' or Quasi-Newton BFGS with constraints. This takes more memory than traditional L-BFGS. The n1qn1 routine is useful since it allows prespecification of a Hessian. If the Hessian is near enough the truth in optimization it can speed up the optimization problem. Both algorithms are described in the 'Scilab' optimization documentation located at <http://www.scilab.org/content/download/250/1714/file/optimization_in_scilab.pdf>.

Ported By: Matthew Fidler, Wenping Wang

Algorithm Authors: C. Lemarechal, Stephen L. Campbell, Jean-Philippe Chancelier, Ramine Nikoukhah

R port of the Scilab n1qn1 module. This package provides n1qn1, or Quasi-Newton BFGS "qn" without constraints. This takes more memory than traditional L-BFGS. This particual routine is useful since it allows prespecification of a Hessian; If the Hessian is near the truth in optimization it can speed up the optimization problem.