sparseHessianFD: Numerical Estimation of Sparse Hessians

Estimates Hessian of a scalar-valued function, and returns it in a sparse Matrix format. The sparsity pattern must be known in advance. The algorithm is especially efficient for hierarchical models with a large number of heterogeneous units.

Version: 0.3.0
Depends: R (≥ 3.2.3)
Imports: Matrix (≥ 1.2.4), methods, Rcpp (≥ 0.12.3)
LinkingTo: Rcpp, RcppEigen (≥ 0.3.2.3)
Suggests: testthat, numDeriv, scales, knitr
Published: 2016-03-15
Author: Michael Braun [aut, cre, cph]
Maintainer: Michael Braun <braunm at smu.edu>
License: MPL (== 2.0)
URL: http://www.smu.edu/Cox/Departments/FacultyDirectory/BraunMichael
NeedsCompilation: yes
SystemRequirements: C++11
Citation: sparseHessianFD citation info
Materials: NEWS
CRAN checks: sparseHessianFD results

Downloads:

Reference manual: sparseHessianFD.pdf
Vignettes: sparseHessianFD
Package source: sparseHessianFD_0.3.0.tar.gz
Windows binaries: r-devel: sparseHessianFD_0.3.0.zip, r-release: sparseHessianFD_0.3.0.zip, r-oldrel: sparseHessianFD_0.2.0.zip
OS X Snow Leopard binaries: r-release: sparseHessianFD_0.1.1.tgz, r-oldrel: sparseHessianFD_0.1.1.tgz
OS X Mavericks binaries: r-release: sparseHessianFD_0.3.0.tgz
Old sources: sparseHessianFD archive

Reverse dependencies:

Reverse suggests: bayesGDS