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C++ Standard Library Vectors in R
Allows the creation and manipulation of C++ std::vector's in R.
C++11 Header Files for 'cereal'
To facilitate using 'cereal' with Rcpp. 'cereal' is a header-only C++11 serialization library. 'cereal' takes arbitrary data types and reversibly turns them into different representations, such as compact binary encodings, XML, or JSON. 'cereal' was designed to be fast, light-weight, and easy to extend - it has no external dependencies and can be easily bundled with other code or used standalone. Please see < http://uscilab.github.io/cereal> for more information.
Data Manipulation Functions Implemented in C
Basic functions, implemented in C, for large data manipulation. Fast vectorised ifelse()/nested if()/switch() functions, psum()/pprod() functions equivalent to pmin()/pmax() plus others which are missing from base R. Most of these functions are callable at C level.
C++ Implementations of Phylogenetic Cladogenesis Calculations
Various cladogenesis-related calculations that are slow in pure R are implemented in C++ with Rcpp. These include the calculation of the probability of various scenarios for the inheritance of geographic range at the divergence events on a phylogenetic tree, and other calculations necessary for models which are not continuous-time markov chains (CTMC), but where change instead occurs instantaneously at speciation events. Typically these models must assess the probability of every possible combination of (ancestor state, left descendent state, right descendent state). This means that there are up to (# of states)^3 combinations to investigate, and in biogeographical models, there can easily be hundreds of states, so calculation time becomes an issue. C++ implementation plus clever tricks (many combinations can be eliminated a priori) can greatly speed the computation time over naive R implementations. CITATION INFO: This package is the result of my Ph.D. research, please cite the package if you use it! Type: citation(package="cladoRcpp") to get the citation information.
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 < http://gallery.rcpp.org> regroups a large number of examples for 'Rcpp'.
'C++' Header Files from 'Abseil'
Wraps the 'Abseil' 'C++' library for use by R packages. Original files are from < https://github.com/abseil/abseil-cpp>. Patches are located at < https://github.com/doccstat/abseil-r/tree/main/local/patches>.
Solving Ax = b Nimbly in C++
Routines for solving large systems of linear equations and eigenproblems in R. Direct and iterative solvers from the Eigen C++ library are made available. Solvers include Cholesky, LU, QR, and Krylov subspace methods (Conjugate Gradient, BiCGSTAB). Dense and sparse problems are supported.
Fast C++ Primitives for the 'NeuroAnatomy Toolbox'
Fast functions implemented in C++ via 'Rcpp' to support the 'NeuroAnatomy Toolbox' ('nat') ecosystem. These functions provide large speed-ups for basic manipulation of neuronal skeletons over pure R functions found in the 'nat' package. The expectation is that end users will not use this package directly, but instead the 'nat' package will automatically use routines from this package when it is available to enable large performance gains.
C++ ODE Solvers Compiled on-Demand
Wraps the Boost odeint library for integration of differential equations.