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: | 0.3.3.7 |
| 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: | 2022-10-19 |
| DOI: | 10.32614/CRAN.package.sparseHessianFD |
| Author: | Michael Braun [aut, cre, cph] |
| Maintainer: | Michael Braun <braunm at smu.edu> |
| BugReports: | https://github.com/braunm/sparseHessianFD/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[issues need fixing before 2025-12-18] |