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: |
0.3.3.2 |
Depends: |
R (≥ 3.4.2) |
Imports: |
Matrix (≥ 1.2.8), methods, Rcpp (≥ 0.12.13) |
LinkingTo: |
Rcpp, RcppEigen (≥ 0.3.3.3.0) |
Suggests: |
testthat, numDeriv, scales, knitr, xtable, dplyr |
Published: |
2017-11-25 |
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 |