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:	0.1.0
Imports:	methods, purrr, rlang, R6, pryr
Suggests:	testthat
Published:	2022-12-21
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

Documentation:

Reference manual:

dfdr.pdf

Downloads:

Package source:	dfdr_0.1.0.tar.gz
Windows binaries:	r-devel: dfdr_0.1.0.zip, r-release: dfdr_0.1.0.zip, r-oldrel: dfdr_0.1.0.zip
macOS binaries:	r-release (arm64): dfdr_0.1.0.tgz, r-oldrel (arm64): dfdr_0.1.0.tgz, r-release (x86_64): dfdr_0.1.0.tgz, r-oldrel (x86_64): dfdr_0.1.0.tgz

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