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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