Found 10000 packages in 0.01 seconds
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.
Import and Export 'SPSS', 'Stata' and 'SAS' Files
Import foreign statistical formats into R via the embedded 'ReadStat' C library, < https://github.com/WizardMac/ReadStat>.
Provides 'mio' C++11 Header Files
Provides header files of 'mio', a cross-platform C++11 header-only library for memory mapped file IO < https://github.com/mandreyel/mio>.
Miscellaneous Functions in C++
Provides utility functions that are simply, frequently used, but may require higher performance that what can be obtained from base R. Incidentally provides support for 'reverse geocoding', such as matching a point with its nearest neighbour in another array. Used as a complement to package 'hutils' by sacrificing compilation or installation time for higher running speeds. The name is a portmanteau of the author and 'Rcpp'.
Misc Functions of the Department of Statistics, Probability Theory Group (Formerly: E1071), TU Wien
Functions for latent class analysis, short time Fourier transform, fuzzy clustering, support vector machines, shortest path computation, bagged clustering, naive Bayes classifier, generalized k-nearest neighbour ...
Random Sampling Distribution C++ Routines for Armadillo
Provides popular sampling distributions C++ routines based in armadillo through a header file approach.
Expanded Replacement and Extension of the 'optim' Function
Provides a replacement and extension of the optim() function to call to several function minimization codes in R in a single statement. These methods handle smooth, possibly box constrained functions of several or many parameters. Note that function 'optimr()' was prepared to simplify the incorporation of minimization codes going forward. Also implements some utility codes and some extra solvers, including safeguarded Newton methods. Many methods previously separate are now included here. This is the version for CRAN.
Low-Level R to Java Interface
Low-level interface to Java VM very much like .C/.Call and friends. Allows creation of objects, calling methods and accessing fields.
R and C/C++ Wrappers to Run the Leiden find_partition() Function
An R to C/C++ interface that runs the Leiden community
detection algorithm to find a basic partition (). It runs the
equivalent of the 'leidenalg' find_partition() function, which is
given in the 'leidenalg' distribution file
'leiden/src/functions.py'. This package includes the
required source code files from the official 'leidenalg'
distribution and functions from the R 'igraph'
package. The 'leidenalg' distribution is available from
< https://github.com/vtraag/leidenalg/>
and the R 'igraph' package is available from
< https://igraph.org/r/>.
The Leiden algorithm is described in the article by
Traag et al. (2019)
Mesh Generation and Surface Tessellation
Makes the 'Qhull' library < http://www.qhull.org> available in R, in a similar manner as in Octave and MATLAB. Qhull computes convex hulls, Delaunay triangulations, halfspace intersections about a point, Voronoi diagrams, furthest-site Delaunay triangulations, and furthest-site Voronoi diagrams. It runs in 2D, 3D, 4D, and higher dimensions. It implements the Quickhull algorithm for computing the convex hull. Qhull does not support constrained Delaunay triangulations, or mesh generation of non-convex objects, but the package does include some R functions that allow for this.