Package: RcppEnsmallen 0.3.11.0.1

James Joseph Balamuta

RcppEnsmallen: Header-Only C++ Mathematical Optimization Library for 'Armadillo'

'Ensmallen' is a templated C++ mathematical optimization library (by the 'MLPACK' team) that provides a simple set of abstractions for writing an objective function to optimize. Provided within are various standard and cutting-edge optimizers that include full-batch gradient descent techniques, small-batch techniques, gradient-free optimizers, and constrained optimization. The 'RcppEnsmallen' package includes the header files from the 'Ensmallen' library and pairs the appropriate header files from 'armadillo' through the 'RcppArmadillo' package. Therefore, users do not need to install 'Ensmallen' nor 'Armadillo' to use 'RcppEnsmallen'. Note that 'Ensmallen' is licensed under 3-Clause BSD, 'Armadillo' starting from 7.800.0 is licensed under Apache License 2, 'RcppArmadillo' (the 'Rcpp' bindings/bridge to 'Armadillo') is licensed under the GNU GPL version 2 or later. Thus, 'RcppEnsmallen' is also licensed under similar terms. Note that 'Ensmallen' requires a compiler that supports 'C++14' and 'Armadillo' 10.8.2 or later.

Authors:James Joseph Balamuta [aut, cre, cph], Dirk Eddelbuettel [aut, cph]

RcppEnsmallen_0.3.11.0.1.tar.gz
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RcppEnsmallen_0.3.11.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION |NEWS
card.svg |card.png
RcppEnsmallen/json (API)

# Install 'RcppEnsmallen' in R:
install.packages('RcppEnsmallen', repos = c('https://coatless-rpkg.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/coatless-rpkg/rcppensmallen/issues

Pkgdown/docs site:https://r-pkg.thecoatlessprofessor.com

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

armadillocpp11ensmallenoptimizationrcpprcpparmadilloopenblascppopenmp

7.76 score 32 stars 15 packages 1 scripts 935 downloads 1 exports 2 dependencies

Last updated from:01aea3c15a. Checks:9 NOTE, 1 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64NOTE135
linux-devel-x86_64NOTE132
source / vignettesOK162
linux-release-arm64NOTE136
linux-release-x86_64NOTE121
macos-release-x86_64NOTE167
macos-oldrel-arm64NOTE86
macos-oldrel-x86_64NOTE230
windows-releaseNOTE111
windows-oldrelNOTE108

Exports:lin_reg_lbfgs

Dependencies:RcppRcppArmadillo

Using RcppEnsmallen in Your Own R Package
Overview | DESCRIPTION file | Makevars inside the src/ Directory

Last update: 2025-09-09
Started: 2023-11-14

Solving Linear Regression using Numeric Optimization
Overview | Linear Regression | Two-Step Implementation | Verifying Results

Last update: 2023-11-14
Started: 2019-09-30