nabla: Exact Derivatives via Automatic Differentiation

Exact automatic differentiation for R functions. Provides a composable derivative operator D that computes gradients, Hessians, Jacobians, and arbitrary-order derivative tensors at machine precision. D(D(f)) gives Hessians, D(D(D(f))) gives third-order tensors for skewness of maximum likelihood estimators, and so on to any order. Works through any R code including loops, branches, and control flow.

Version: 0.7.1
Depends: R (≥ 4.0.0), methods
Imports: stats
Suggests: testthat (≥ 3.0.0), knitr, rmarkdown
Published: 2026-02-10
DOI: 10.32614/CRAN.package.nabla (may not be active yet)
Author: Alexander Towell ORCID iD [aut, cre]
Maintainer: Alexander Towell <queelius at gmail.com>
BugReports: https://github.com/queelius/nabla/issues
License: MIT + file LICENSE
URL: https://github.com/queelius/nabla, https://metafunctor.com
NeedsCompilation: no
Citation: nabla citation info
Materials: README, NEWS
CRAN checks: nabla results

Documentation:

Reference manual: nabla.html , nabla.pdf
Vignettes: Higher-Order Derivatives (source, R code)
Introduction to nabla (source, R code)
Higher-Order MLE Analysis (source, R code)
Gradient and Hessian Computation with nabla (source, R code)
Optimizer Integration (source, R code)

Downloads:

Package source: nabla_0.7.1.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): nabla_0.7.1.tgz, r-oldrel (arm64): nabla_0.7.1.tgz, r-release (x86_64): nabla_0.7.1.tgz, r-oldrel (x86_64): nabla_0.7.1.tgz

Linking:

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