CRAN packages

'Rcpp' Integration for the 'Eigen' Templated Linear Algebra Library. R and 'Eigen' integration using 'Rcpp'. 'Eigen' is a C++ template library for linear algebra: matrices, vectors, numerical solvers and related algorithms. It supports dense and sparse matrices on integer, floating point and complex numbers, decompositions of such matrices, and solutions of linear s

Manage the Life Cycle of your Package Functions. Manage the life cycle of your exported functions with shared conventions, documentation badges, and user-friendly deprecation warnings.

Create Elegant Data Visualisations Using the Grammar of Graphics. A system for 'declaratively' creating graphics, based on "The Grammar of Graphics". You provide the data, tell 'ggplot2' how to map variables to aesthetics, what graphical primitives to use, and it takes care of the details.

Seamless R and C++ Integration. The 'Rcpp' package provides R functions as well as C++ classes which offer a seamless integration of R and C++. Many R data types and objects can be mapped back and forth to C++ equivalents which facilitates both writing of new code as well as easier integration of third-party libraries. Documentati

Parallel Programming Tools for 'Rcpp'. High level functions for parallel programming with 'Rcpp'. For example, the 'parallelFor()' function can be used to convert the work of a standard serial "for" loop into a parallel one and the 'parallelReduce()' function can be used for accumulating aggregate or other values.

Encapsulated Classes with Reference Semantics. Creates classes with reference semantics, similar to R's built-in reference classes. Compared to reference classes, R6 classes are simpler and lighter-weight, and they are not built on S4 classes so they do not require the methods package. These classes allow public and private members, and they sup

Interpreted String Literals. An implementation of interpreted string literals, inspired by Python's Literal String Interpolation <https://www.python.org/dev/peps/pep-0498/> and Docstrings <https://www.python.org/dev/peps/pep-0257/> and Julia's Triple-Quoted String Literals <https://docs.julialang.org/en/v1.3/manual/strings/#Tri

Cross-Platform File System Operations Based on 'libuv'. A cross-platform interface to file system operations, built on top of the 'libuv' C library.

Run Code 'With' Temporarily Modified Global State. A set of functions to run code 'with' safely and temporarily modified global state. Many of these functions were originally a part of the 'devtools' package, this provides a simple package with limited dependencies to provide access to these functions.

Simple Data Frames. Provides a 'tbl_df' class (the 'tibble') with stricter checking and better formatting than the traditional data frame.

A Forward-Pipe Operator for R. Provides a mechanism for chaining commands with a new forward-pipe operator, %>%. This operator will forward a value, or the result of an expression, into the next function call/expression. There is flexible support for the type of right-hand side expressions. For more information, see package vigne

C++ Header Files for Stan. The C++ header files of the Stan project are provided by this package, but it contains little R code or documentation. The main reference is the vignette. There is a shared object containing part of the 'CVODES' library, but its functionality is not accessible from R. 'StanHeaders' is primarily usef

Coloured Formatting for Columns. Provides 'pillar' and 'colonnade' generics designed for formatting columns of data using the full range of colours provided by modern terminals.

A C++11 Interface for R's C Interface. Provides a header only, C++11 interface to R's C interface. Compared to other approaches 'cpp11' strives to be safe against long jumps from the C API as well as C++ exceptions, conform to normal R function semantics and supports interaction with 'ALTREP' vectors.

A Simple and Robust JSON Parser and Generator for R. A reasonably fast JSON parser and generator, optimized for statistical data and the web. Offers simple, flexible tools for working with JSON in R, and is particularly powerful for building pipelines and interacting with a web API. The implementation is based on the mapping described in the vignette

R Interface to Stan. User-facing R functions are provided to parse, compile, test, estimate, and analyze Stan models by accessing the header-only Stan library provided by the 'StanHeaders' package. The Stan project develops a probabilistic programming language that implements full Bayesian statistical inference via Mark

Dynamic Documents for R. Convert R Markdown documents into a variety of formats.