ADtools
0.5.4Automatic Differentiation Toolbox
Overview
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.
Install
Health
CRAN check results are not tracked yet.
Downloads
Dependencies
Nothing depends on this yet.
Code & Tests
- Cyclomatic complexity
- 1.0 median / 7 max
- Test cases
- 55 / 0.38 per code line
- Documented parameters
- 100%
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
143 44 exported
Complexity
1.6 avg / 7 max
Call network
143 nodes / 101 edges
Test coverage has not been measured for this package yet; nodes fall back to a neutral fill.
Call graph
Open call graph →Lowest coverage
Per-function coverage is not measured for this package yet.
People & History
1 release. R releases are shown for context.
- RR 4.2.0 released · 2022-04-22
- archivedRemoved from CRAN2021-07-25email to the maintainer is undeliverable when asked to use a suggested package conditionally
- RR 4.1.0 released · 2021-05-18
- 0.5.42020-11-09
- RR 4.0.0 released · 2020-04-24
Package metadata
- Total releases
- 1
- License
- MIT + file LICENSE OSI
- Minimum R
- ≥ 3.6.0
- Download size
- not tracked yet
- Installed size
- not tracked yet
- With dependencies
- not tracked yet