Package: sparseHessianFD
Type: Package
Title: Interface to ACM TOMS Algorithm 636, for computing sparse
        Hessians.
Version: 0.1.0
Date: 2012-11-15
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@mit.edu>
URL: braunm.scripts.mit.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 when
        optimizing objective functions using optimizers than can
        exploit this sparsity, such as the trustOptim package. The
        underlying algorithm is ACM TOMS Algorithm 636, written by
        Coleman, Garbow and More (ACM Transactions on Mathematical
        Software, 11:4, Dec. 1985). The package also includes functions
        to sample from, and compute the log density of, a multivariate
        normal distribution when the precision matrix is sparse.
License: file LICENSE
Depends: Rcpp (>= 0.9.6), RcppEigen (>= 0.3.1), Matrix, methods
LinkingTo: Rcpp, RcppEigen
Packaged: 2012-11-26 17:32:23 UTC; braunm
Repository: CRAN
Date/Publication: 2012-11-26 19:09:55
NeedsCompilation: yes
License_restricts_use: yes
