Package: sparseHessianFD
Type: Package
Title: Numerical estimation of sparse Hessians using ACM TOMS Algorithm
        636.
Version: 0.1.1
Date: 2013-11-05
Author: R interface code by Michael Braun
	Original Fortran code by Thomas F. Coleman, Burton S. Garbow and
	Jorge J. More.
Maintainer: Michael Braun <braunm@smu.edu>
URL: mbraun.cox.smu.edu
Description: Computes Hessian of a scalar-valued function, and returns it in sparse Matrix format.
	      The user must supply the objective function, the 
	      gradient, and the row and column indices of the non-zero elements of the lower
	      triangle of the Hessian (i.e., the sparsity structure must be known in advance).
	      The algorithm exploits this sparsity, so Hessians can be computed quickly even
	      when the number of arguments to the objective functions is large. This package is
	      intended to be useful for numeric optimization (e.g., with the trustOptim package) 
	      or in simulation (e.g., the sparseMVN package). The underlying algorithm is ACM TOMS
	      Algorithm 636, written by Coleman, Garbow and More (ACM Transactions on Mathematical
	      Software, 11:4, Dec. 1985).
License: file LICENSE
Depends: Rcpp (>= 0.9.6), RcppEigen (>= 0.3.1), Matrix, methods
Suggests: plyr
LinkingTo: Rcpp, RcppEigen
Packaged: 2013-11-05 23:48:32 UTC; braunm
NeedsCompilation: yes
License_restricts_use: yes
Repository: CRAN
Date/Publication: 2013-11-06 07:16:04
Built: R 3.1.0; x86_64-apple-darwin10.8.0; 2013-11-28 04:02:57 UTC; unix
Archs: sparseHessianFD.so.dSYM
