Sparse Matrix C++ Classes Including Sparse Cholesky LDL Decomposition of Symmetric Matrices

'C++' classes for sparse matrix methods including implementation of sparse LDL decomposition of symmetric matrices and solvers described by Timothy A. Davis (2016) < https://fossies.org/linux/SuiteSparse/LDL/Doc/ldl_userguide.pdf>. Provides a set of C++ classes for basic sparse matrix specification and linear algebra, and a class to implement sparse LDL decomposition and solvers. See < https://github.com/samuel-watson/SparseChol> for details.

Minimal Interface of the C++ 'MixtComp' Library for Mixture Models with Heterogeneous and (Partially) Missing Data

Mixture Composer < https://github.com/modal-inria/MixtComp> is a project to build mixture models with heterogeneous data sets and partially missing data management. It includes models for real, categorical, counting, functional and ranking data. This package contains the minimal R interface of the C++ 'MixtComp' library.

'R' Bindings to the 'C' Grammar for Tree-Sitter

Provides bindings to a 'C' grammar for Tree-sitter, to be used alongside the 'treesitter' package. Tree-sitter builds concrete syntax trees for source files and can efficiently update them or generate code like producing R C API wrappers from C functions, structs and global definitions from header files.

'C++' Header Library for Ordinary Differential Equations

A 'C++' header library for using the 'libsoda-cxx' library with R. The 'C++' header reimplements the 'lsoda' function from the 'ODEPACK' library for solving initial value problems for first order ordinary differential equations (Hindmarsh, 1982; < https://computing.llnl.gov/sites/default/files/ODEPACK_pub1_u88007.pdf>). The 'C++' header can be used by other R packages by linking against this package. The 'C++' functions can be called inline using 'Rcpp'. Finally, the package provides an 'ode' function to call from R.

C Resource Cleanup via Exit Handlers

Wrapper of .Call() that runs exit handlers to clean up C resources. Helps managing C (non-R) resources while using the R API.

Examples using 'Rcpp' to Interface R and C++

Examples for Seamless R and C++ integration The 'Rcpp' package contains a C++ library that facilitates the integration of R and C++ in various ways. This package provides some usage examples. Note that the documentation in this package currently does not cover all the features in the package. The site < https://gallery.rcpp.org> regroups a large number of examples for 'Rcpp'.

A Compendium of Bayesian Statistical Routines Written in 'C++'

This is a compendium of 'C++' routines useful for Bayesian statistics. We steal other people's 'C++' code, repurpose it, and export it so developers of 'R' packages can use it in their 'C++' code. We actually don't steal anything, or claim that Thomas Bayes did, but copy code that is compatible with our GPL 3 licence, fully acknowledging the authorship of the original code.

Derivative-Free Optimization in R using C++

Perform derivative-free optimization algorithms in R using C++. A wrapper interface is provided to call C function of the 'bobyqa' implementation (See < https://github.com/emmt/Algorithms/tree/master/bobyqa>).

Fast R and C++ Access to NIfTI Images

Provides very fast read and write access to images stored in the NIfTI-1, NIfTI-2 and ANALYZE-7.5 formats, with seamless synchronisation of in-memory image objects between compiled C and interpreted R code. Also provides a simple image viewer, and a C/C++ API that can be used by other packages. Not to be confused with 'RNiftyReg', which performs image registration and applies spatial transformations.

Forward Selection using Concordance/C-Index

Performs forward model selection, using the C-index/concordance in survival analysis models.