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.

Version: 0.2.0
Imports: methods, purrr, rlang, R6, pryr
Suggests: tinytest
Published: 2023-02-23
DOI: 10.32614/CRAN.package.dfdr
Author: Thomas Mailund [aut], Konrad Krämer [aut, cre]
Maintainer: Konrad Krämer <konrad_kraemer at yahoo.de>
License: GPL-3
NeedsCompilation: no
CRAN checks: dfdr results


Reference manual: dfdr.pdf


Package source: dfdr_0.2.0.tar.gz
Windows binaries: r-devel: dfdr_0.2.0.zip, r-release: dfdr_0.2.0.zip, r-oldrel: dfdr_0.2.0.zip
macOS binaries: r-release (arm64): dfdr_0.2.0.tgz, r-oldrel (arm64): dfdr_0.2.0.tgz, r-release (x86_64): dfdr_0.2.0.tgz, r-oldrel (x86_64): dfdr_0.2.0.tgz
Old sources: dfdr archive

Reverse dependencies:

Reverse imports: ast2ast, paropt


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