pnd: Parallel Numerical Derivatives, Gradients, Jacobians, and Hessians of Arbitrary Accuracy Order

Numerical derivatives through finite-difference approximations can be calculated using the 'pnd' package with parallel capabilities and optimal step-size selection to improve accuracy. These functions facilitate efficient computation of derivatives, gradients, Jacobians, and Hessians, allowing for more evaluations to reduce the mathematical and machine errors. Designed for compatibility with the 'numDeriv' package, which has not received updates in several years, it introduces advanced features such as computing derivatives of arbitrary order, improving the accuracy of Hessian approximations by avoiding repeated differencing, and parallelising slow functions on Windows, Mac, and Linux.

Version:	0.0.8
Depends:	R (≥ 3.4.0)
Imports:	parallel, Rdpack
Suggests:	numDeriv, knitr, rmarkdown, testthat (≥ 3.0.0)
Published:	2025-03-06
DOI:	10.32614/CRAN.package.pnd
Author:	Andreï Victorovitch Kostyrka [aut, cre]
Maintainer:	Andreï Victorovitch Kostyrka <andrei.kostyrka at gmail.com>
BugReports:	https://github.com/Fifis/pnd/issues
License:	EUPL
URL:	https://github.com/Fifis/pnd
NeedsCompilation:	no
Citation:	pnd citation info
Materials:	README NEWS
CRAN checks:	pnd results

Documentation:

Reference manual:	pnd.pdf
Vignettes:	Compatilibility of pnd with the syntax of numDeriv (source, R code) Fast and accurate parallel numerical derivatives in R (source, R code) Step-size-selection algorithm benchmark (source, R code)

Downloads:

Package source:	pnd_0.0.8.tar.gz
Windows binaries:	r-devel: pnd_0.0.8.zip, r-release: pnd_0.0.8.zip, r-oldrel: pnd_0.0.8.zip
macOS binaries:	r-devel (arm64): pnd_0.0.8.tgz, r-release (arm64): pnd_0.0.8.tgz, r-oldrel (arm64): pnd_0.0.8.tgz, r-devel (x86_64): pnd_0.0.8.tgz, r-release (x86_64): pnd_0.0.8.tgz, r-oldrel (x86_64): pnd_0.0.8.tgz
Old sources:	pnd archive

Linking:

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