dual: Automatic Differentiation with Dual Numbers
Automatic differentiation is achieved by using dual numbers without
providing hand-coded gradient functions. The output value of a mathematical
function is returned with the values of its exact first derivative
(or gradient). For more details see Baydin, Pearlmutter, Radul, and Siskind
(2018) <https://jmlr.org/papers/volume18/17-468/17-468.pdf>.
| Version: |
0.0.6 |
| Depends: |
R (≥ 3.2.0), base, stats, methods |
| Published: |
2025-05-28 |
| DOI: |
10.32614/CRAN.package.dual |
| Author: |
Luca Sartore [aut] (ORCID = "0000-0002-0446-1328"),
Luca Sartore [cre] (ORCID = "0000-0002-0446-1328") |
| Maintainer: |
Luca Sartore <drwolf85 at gmail.com> |
| License: |
GPL-3 |
| NeedsCompilation: |
no |
| Materials: |
README, ChangeLog |
| In views: |
NumericalMathematics |
| CRAN checks: |
dual results |
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