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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.
Template Model Builder: A General Random Effect Tool Inspired by 'ADMB'
With this tool, a user should be able to quickly implement complex random effect models through simple C++ templates. The package combines 'CppAD' (C++ automatic differentiation), 'Eigen' (templated matrix-vector library) and 'CHOLMOD' (sparse matrix routines available from R) to obtain an efficient implementation of the applied Laplace approximation with exact derivatives. Key features are: Automatic sparseness detection, parallelism through 'BLAS' and parallel user templates.
Regression Spline Functions and Classes
Constructs basis functions of B-splines, M-splines,
I-splines, convex splines (C-splines), periodic splines,
natural cubic splines, generalized Bernstein polynomials,
their derivatives, and integrals (except C-splines)
by closed-form recursive formulas.
It also contains a C++ head-only library integrated with Rcpp.
See Wang and Yan (2021)
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.
Primal or Dual Cone Projections with Routines for Constrained Regression
Routines doing cone projection and quadratic programming, as well as doing estimation and inference for constrained parametric regression and shape-restricted regression problems. See Mary C. Meyer (2013)
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>).
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'.
Forward Selection using Concordance/C-Index
Performs forward model selection, using the C-index/concordance in survival analysis models.