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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.
T-Distributed Stochastic Neighbor Embedding using a Barnes-Hut Implementation
An R wrapper around the fast T-distributed Stochastic Neighbor Embedding implementation by Van der Maaten (see < https://github.com/lvdmaaten/bhtsne/> for more information on the original implementation).
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)
Wrapper for 'lz-string' 'C++' Library
Provide access to the 'lz-string' < http://pieroxy.net/blog/pages/lz-string/index.html> 'C++' library for Lempel-Ziv (LZ) based compression and decompression of strings.
'R' Access to the 'tskit C' API
'Tskit' enables efficient storage, manipulation, and analysis
of ancestral recombination graphs (ARGs) using succinct tree sequence
encoding. The tree sequence encoding of an ARG is described in Wong et
al. (2024)
'C++' Standard Template Library Containers
Use 'C++' Standard Template Library containers interactively in R. Includes sets, unordered sets, multisets, unordered multisets, maps, unordered maps, multimaps, unordered multimaps, stacks, queues, priority queues, vectors, deques, forward lists, and lists.
Translates an R Function to a C++ Function
Enable translation of a tiny subset of R to C++. The user has to define a R function which gets translated. For a full list of possible functions check the documentation. After translation an R function is returned which is a shallow wrapper around the C++ code. Alternatively an external pointer to the C++ function is returned to the user. The intention of the package is to generate fast functions which can be used as ode-system or during optimization.
C++ Standard Library Vectors in R
Allows the creation and manipulation of C++ std::vector's in R.
Capture Hi-C Analysis Engine
Toolkit for processing and calling interactions in capture Hi-C data. Converts BAM files into counts of reads linking restriction fragments, and identifies pairs of fragments that interact more than expected by chance. Significant interactions are identified by comparing the observed read count to the expected background rate from a count regression model.