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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: |
0.3.3.7 |
| 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 |
Documentation:
Downloads:
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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