Software / Code

ADtools: Automatic Differentiation Toolbox. R package version 0.5.5

Chun Fung Kwok, Dan Zhu, Liana Jacobi

ADtools | Published : 2020

Abstract

Implements the forward-mode automatic differentiation for multivariate functions using the matrix-calculus notation from Magnus and Neudecker (2019) . 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.

University of Melbourne Researchers