Package: RcppFastAD 0.0.2

RcppFastAD: 'Rcpp' Bindings to 'FastAD' Auto-Differentiation

The header-only 'C++' template library 'FastAD' for automatic differentiation <https://github.com/JamesYang007/FastAD> is provided by this package, along with a few illustrative examples that can all be called from R.

Authors:Dirk Eddelbuettel [aut, cre], James Yang [aut]

RcppFastAD_0.0.2.tar.gz
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RcppFastAD.pdf |RcppFastAD.html✨
RcppFastAD/json (API)
NEWS

# Install 'RcppFastAD' in R:

install.packages('RcppFastAD', repos = c('https://eddelbuettel.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/eddelbuettel/rcppfastad/issues

Uses libs:

c++– GNU Standard C++ Library v3

On CRAN:

3 exports 8 stars 1.52 score 2 dependencies 161 downloads

Last updated 2 months agofrom:cac9541adc

Exports:black_scholes linear_regression quadratic_expression

Dependencies:Rcpp RcppEigen

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
'Rcpp' Bindings to 'FastAD' Auto-Differentiation	RcppFastAD-package RcppFastAD
Black-Scholes valuation and first derivatives via Automatic Differentiation	black_scholes
Evaluate a squared-loss linear regression at a given parameter value	linear_regression
Compute the value and derivate of a quadratic expression X' * Sigma * X	quadratic_expression