Package: dfdr 0.2.0

dfdr: Automatic Differentiation of Simple Functions

Implementation of automatically computing derivatives of functions (see Mailund Thomas (2017) <doi:10.1007/978-1-4842-2881-4>). Moreover, calculating gradients, Hessian and Jacobian matrices is possible.

Authors:Thomas Mailund [aut], Konrad Krämer [aut, cre]

dfdr_0.2.0.tar.gz
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dfdr.pdf |dfdr.html✨
dfdr/json (API)

# Install 'dfdr' in R:
install.packages('dfdr', repos = c('https://konrad1991.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/konrad1991/dfdr/issues

On CRAN:

4.66 score 7 stars 2 packages 11 scripts 222 downloads 7 exports 17 dependencies

Last updated 2 years agofrom:166ce20aed. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 04 2024
R-4.5-winOKNov 04 2024
R-4.5-linuxOKNov 04 2024
R-4.4-winOKNov 04 2024
R-4.4-macOKNov 04 2024
R-4.3-winOKNov 04 2024
R-4.3-macOKNov 04 2024

Exports:dfctsfcts_add_fctgradienthessianjacobiansimplify

Dependencies:clicodetoolscpp11crayongluelifecyclelobstrmagrittrprettyunitspryrpurrrR6Rcpprlangstringistringrvctrs