ADtools: Automatic Differentiation Toolbox

Implements the forward-mode automatic differentiation for multivariate functions using the matrix-calculus notation from Magnus and Neudecker (2019) <doi:10.1002/9781119541219>. Two key features of the package are: (i) it incorporates various optimisation strategies to improve performance; this includes applying memoisation to cut down object construction time, using sparse matrix representation to speed up derivative calculation, and creating specialised matrix operations to reduce computation time; (ii) it supports differentiating random variates with respect to their parameters, targeting Markov chain Monte Carlo (MCMC) and general simulation-based applications.

Package details

AuthorChun Fung Kwok [aut, cre] (<>), Dan Zhu [aut] (<>), Liana Jacobi [aut] (<>)
MaintainerChun Fung Kwok <>
LicenseMIT + file LICENSE
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:

Try the ADtools package in your browser

Any scripts or data that you put into this service are public.

ADtools documentation built on Nov. 9, 2020, 5:09 p.m.