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. See Braun, M. (2017) <doi:10.18637/jss.v082.i10>.

Version: 0.3.3.6
Depends: R (≥ 4.0.0)
Imports: Matrix (≥ 1.4), methods, Rcpp (≥ 0.12.13)
LinkingTo: Rcpp, RcppEigen (≥ 0.3.3.3.0)
Suggests: testthat, numDeriv, scales, knitr, xtable, dplyr
Published: 2022-08-16
Author: Michael Braun ORCID iD [aut, cre, cph]
Maintainer: Michael Braun <braunm at smu.edu>
BugReports: https://github.com/braunm/trustOptim/issues/
License: MPL (== 2.0)
URL: https://braunm.github.io/sparseHessianFD/, https://github.com/braunm/sparseHessianFD/
NeedsCompilation: yes
SystemRequirements: C++11
Citation: sparseHessianFD citation info
Materials: NEWS
CRAN checks: sparseHessianFD results

Documentation:

Reference manual: sparseHessianFD.pdf
Vignettes: sparseHessianFD

Downloads:

Package source: sparseHessianFD_0.3.3.6.tar.gz
Windows binaries: r-devel: sparseHessianFD_0.3.3.6.zip, r-release: sparseHessianFD_0.3.3.6.zip, r-oldrel: sparseHessianFD_0.3.3.5.zip
macOS binaries: r-release (arm64): sparseHessianFD_0.3.3.6.tgz, r-oldrel (arm64): sparseHessianFD_0.3.3.6.tgz, r-release (x86_64): sparseHessianFD_0.3.3.5.tgz, r-oldrel (x86_64): sparseHessianFD_0.3.3.5.tgz
Old sources: sparseHessianFD archive

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