C++ ODE Solvers Compiled on-Demand

Wraps the Boost odeint library for integration of differential equations.

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.

Toolbox for Pseudo and Quasi Random Number Generation and Random Generator Tests

Provides (1) pseudo random generators - general linear congruential generators, multiple recursive generators and generalized feedback shift register (SF-Mersenne Twister algorithm () and WELL () generators); (2) quasi random generators - the Torus algorithm, the Sobol sequence, the Halton sequence (including the Van der Corput sequence) and (3) some generator tests - the gap test, the serial test, the poker test, see, e.g., Gentle (2003) . Take a look at the Distribution task view of types and tests of random number generators. The package can be provided without the 'rngWELL' dependency on demand. Package in Memoriam of Diethelm and Barbara Wuertz.

Bayesian Applied Regression Modeling via Stan

Estimates previously compiled regression models using the 'rstan' package, which provides the R interface to the Stan C++ library for Bayesian estimation. Users specify models via the customary R syntax with a formula and data.frame plus some additional arguments for priors.

'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 as files are edited.

'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.