[aut, cre]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) <http://jmlr.org/papers/volume18/17-468/17-468.pdf>.
| Version: | 0.0.3 |
| Depends: | R (≥ 3.2.0), base, stats, methods |
| Published: | 2019-12-18 |
| Author: | Luca Sartore
[aut, cre] |
| Maintainer: | Luca Sartore <drwolf85 at gmail.com> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| Materials: | README ChangeLog |
| In views: | NumericalMathematics |
| CRAN checks: | dual results |
| Reference manual: | dual.pdf |
| Package source: | dual_0.0.3.tar.gz |
| Windows binaries: | r-devel: dual_0.0.3.zip, r-release: dual_0.0.3.zip, r-oldrel: dual_0.0.3.zip |
| macOS binaries: | r-release: dual_0.0.3.tgz, r-oldrel: dual_0.0.3.tgz |
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