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: | 0.3.3.4 |
Depends: | R (≥ 3.4.0) |
Imports: | Matrix (≥ 1.2.12), methods, Rcpp (≥ 0.12.13) |
LinkingTo: | Rcpp, RcppEigen (≥ 0.3.3.3.0) |
Suggests: | testthat, numDeriv, scales, knitr, xtable, dplyr |
Published: | 2019-03-06 |
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 |
Reference manual: | sparseHessianFD.pdf |
Vignettes: |
sparseHessianFD |
Package source: | sparseHessianFD_0.3.3.4.tar.gz |
Windows binaries: | r-devel: sparseHessianFD_0.3.3.4.zip, r-release: sparseHessianFD_0.3.3.4.zip, r-oldrel: sparseHessianFD_0.3.3.4.zip |
macOS binaries: | r-release: sparseHessianFD_0.3.3.4.tgz, r-oldrel: sparseHessianFD_0.3.3.4.tgz |
Old sources: | sparseHessianFD archive |
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