radx
Package radx. 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.
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References in zbMATH (referenced in 2 articles )
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Sorted by year (- Kulshreshtha, K.; Narayanan, S. H. K.; Bessac, J.; MacIntyre, K.: Efficient computation of derivatives for solving optimization problems in R and Python using SWIG-generated interfaces to ADOL-C (2018)
- Härdle, Karl Wolfgang; Okhrin, Ostap; Okhrin, Yarema: Basic elements of computational statistics (2017)