This package provides mathematical functions that are able to handle computations with dual numbers. Dual numbers are mainly used to implement automatic differentiation. The package is useful to calculate exact derivatives in R without providing hand-coded gradient functions. Kisil (2007) <arXiv:0707.4024>
For a complete list of exported functions, use
library(help = "dual").
Luca Sartore firstname.lastname@example.org
Maintainer: Luca Sartore email@example.com
Baydin, A. G., Pearlmutter, B. A., Radul, A. A., & Siskind, J. M. (2018). Automatic differentiation in machine learning: a survey. Journal of Marchine Learning Research, 18, 1-43.
Cheng, H. H. (1994). Programming with dual numbers and its applications in mechanisms design. Engineering with Computers, 10(4), 212-229.
library(dual) x <- dual(f = 1.5, grad = c(1, 0, 0)) y <- dual(f = 0.5, grad = c(0, 1, 0)) z <- dual(f = 1.0, grad = c(0, 0, 1)) exp(z - x) * sin(x)^y / x a <- dual(1.1, grad = c(1.2, 2.3, 3.4, 4.5, 5.6)) 0.5 * a^2 - 0.1
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