Automatic Differentiation in R
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Latest commit 26fe58c Aug 14, 2010 chillu chillu Add demo showing usage of radxeval

README

Automatic Differentiation in R

rdx is a package to compute derivatives (of any order) of native R code
for multivariate functions with vector outputs, f:R^m → R^n, through
Automatic Differentiation (AD). Numerical evaluation of derivatives
has widespread uses in many fields. rdx will implement two modes for
the computation of derivatives, the Forward and Reverse modes of AD,
combining which we can efficiently compute Jacobians and Hessians. Higher
order derivatives will be evaluated through Univariate Taylor Propagation.

TODO:
* Implement both forward and reverse mode of automatic differentiation
* Evaluation of first and higher order derivatives of vector functions
* Compute higher order derivatives very quickly
* Derivative matrices - Jacobians, Hessians
* Write a unit test suite