madness: Automatic Differentiation of Multivariate Operations

An object that supports automatic differentiation of matrix- and multidimensional-valued functions with respect to multidimensional independent variables. Automatic differentiation is via 'forward accumulation'.

Version: 0.2.7
Depends: R (≥ 3.2.0)
Imports: Matrix, matrixcalc, expm, methods
Suggests: testthat, dplyr, tidyr, lubridate, SharpeR, sandwich, formatR, knitr
Published: 2020-02-08
Author: Steven E. Pav ORCID iD [aut, cre]
Maintainer: Steven E. Pav <shabbychef at gmail.com>
BugReports: https://github.com/shabbychef/madness/issues
License: LGPL-3
URL: https://github.com/shabbychef/madness
NeedsCompilation: no
Citation: madness citation info
Materials: README ChangeLog
CRAN checks: madness results

Documentation:

Reference manual: madness.pdf
Vignettes: Asymptotic Distribution of the Markowitz Portfolio

Downloads:

Package source: madness_0.2.7.tar.gz
Windows binaries: r-devel: madness_0.2.7.zip, r-release: madness_0.2.7.zip, r-oldrel: madness_0.2.7.zip
macOS binaries: r-release (arm64): madness_0.2.7.tgz, r-oldrel (arm64): madness_0.2.7.tgz, r-release (x86_64): madness_0.2.7.tgz, r-oldrel (x86_64): madness_0.2.7.tgz
Old sources: madness archive

Reverse dependencies:

Reverse depends: rjmcmc
Reverse imports: BayesOrdDesign

Linking:

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