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Testing for Change in C-Statistic
Calculate the confidence interval and p value for change in C-statistic. The adjusted C-statistic is calculated by using formula as "Somers' Dxy rank correlation"/2+0.5. The confidence interval was calculated by using the bootstrap method. The p value was calculated by using the Z testing method. Please refer to the article of Peter Ganz et al. (2016)
'TinyDNG' C++ Header Files
Provides C++ header files for 'TinyDNG', a small header-only library for reading and writing 'DNG' and 'TIFF' files.
C++ Tools for Cleaning Strings
Provides function declarations and inline function definitions that facilitate cleaning strings in C++ code before passing them to R.
Interface to the 'C++' Library 'Pf'
Builds and runs 'c++' code for classes that encapsulate state space model, particle filtering algorithm pairs.
Algorithms include the Bootstrap Filter from Gordon et al. (1993)
C R Bytecode Compiler
Implements a bytecode compiler for 'R' in 'C', targeting functional parity with the base 'compiler' package, while focusing on better performance. The architecture mostly mirrors the original 'GNU-R' compiler as described in < https://homepage.cs.uiowa.edu/~luke/R/compiler/compiler.pdf>.
Distribution of the 'BayesX' C++ Sources
'BayesX' performs Bayesian inference in structured additive regression (STAR) models. The R package BayesXsrc provides the 'BayesX' command line tool for easy installation. A convenient R interface is provided in package R2BayesX.
Matching Algorithms in R and C++
Computes matching algorithms quickly using Rcpp. Implements the Gale-Shapley Algorithm to compute the stable matching for two-sided markets, such as the stable marriage problem and the college-admissions problem. Implements Irving's Algorithm for the stable roommate problem. Implements the top trading cycle algorithm for the indivisible goods trading problem.
Split, Combine and Compress PDF Files
Content-preserving transformations transformations of PDF files such as split, combine, and compress. This package interfaces directly to the 'qpdf' C++ library < https://qpdf.sourceforge.io/> and does not require any command line utilities. Note that 'qpdf' does not read actual content from PDF files: to extract text and data you need the 'pdftools' package.
Advanced and Fast Data Transformation
A large C/C++-based package for advanced data transformation and
statistical computing in R that is extremely fast, class-agnostic, robust, and
programmer friendly. Core functionality includes a rich set of S3 generic grouped
and weighted statistical functions for vectors, matrices and data frames, which
provide efficient low-level vectorizations, OpenMP multithreading, and skip missing
values by default. These are integrated with fast grouping and ordering algorithms
(also callable from C), and efficient data manipulation functions. The package also
provides a flexible and rigorous approach to time series and panel data in R, fast
functions for data transformation and common statistical procedures, detailed
(grouped, weighted) summary statistics, powerful tools to work with nested data,
fast data object conversions, functions for memory efficient R programming, and
helpers to effectively deal with variable labels, attributes, and missing data. It
seamlessly supports base R objects/classes as well as 'units', 'integer64', 'xts'/
'zoo', 'tibble', 'grouped_df', 'data.table', 'sf', and 'pseries'/'pdata.frame'.
For a concise overview of the package see Krantz (2026)
HTTP and WebSocket Server Library
Provides low-level socket and protocol support for handling HTTP and WebSocket requests directly from within R. It is primarily intended as a building block for other packages, rather than making it particularly easy to create complete web applications using httpuv alone. httpuv is built on top of the libuv and http-parser C libraries, both of which were developed by Joyent, Inc. (See LICENSE file for libuv and http-parser license information.)