Package {Rcppautodiff}

Type:	Package
Title:	An Interface to the C++ Automatic Differentiation Library 'autodiff'
Version:	0.1.0
Date:	2026-06-27
Maintainer:	Satyaprakash Nayak <satyaprakash.nayak@gmail.com>
URL:	https://github.com/sn248/Rcppautodiff, https://sn248.github.io/Rcppautodiff/
BugReports:	https://github.com/sn248/Rcppautodiff/issues
Description:	Provides an interface from R to the 'autodiff' library https://autodiff.github.io/, a modern header-only C++ library for automatic differentiation. Unlike numerical differentiation, automatic differentiation computes derivatives of functions to machine precision without truncation error, using either forward or reverse mode. The 'autodiff' header files are shipped with this package so that other R packages can use them by including 'Rcppautodiff' in the 'LinkingTo' field of their 'DESCRIPTION' file. Example programs demonstrate computing derivatives of single-variable and multi-variable functions, gradient vectors, Jacobian matrices and derivatives with respect to parameters, using 'Rcpp' and 'RcppEigen'.
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
Suggests:	knitr, rmarkdown, tinytest
Encoding:	UTF-8
Imports:	Rcpp (≥ 1.0.8.3), RcppEigen
LinkingTo:	Rcpp, RcppEigen
VignetteBuilder:	knitr
Config/roxygen2/version:	8.0.0
NeedsCompilation:	yes
Packaged:	2026-07-09 23:00:58 UTC; quantilogy
Author:	Satyaprakash Nayak [aut, cre]
Repository:	CRAN
Date/Publication:	2026-07-19 12:40:08 UTC

autodiff_single_var

Description

Example function to show differentiation w.r.t. a single variable

Usage

autodiff_single_var(input)

Arguments

Value

A named list with two elements, value (the function f(x) = 1 + x + x^2 + 1/x + \log(x) evaluated at input) and derivative (the derivative of f evaluated at input).

Examples

res <- autodiff_single_var(2.0)
res$value        # f(2)  = 1 + 2 + 4 + 0.5 + log(2)
res$derivative   # f'(2) = 1 + 4 - 0.25 + 0.5 = 5.25