Examples: visualization, C++, networks, data cleaning, html widgets, ropensci.

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TMB — by Kasper Kristensen, 3 months ago

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.

qpdf — by Jeroen Ooms, 3 months ago

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.

lzstring — by Sam Parmar, 21 days ago

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.

cppcontainers — by Christian Düben, 5 months ago

'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.

stdvectors — by Marco Giuliano, 8 years ago

C++ Standard Library Vectors in R

Allows the creation and manipulation of C++ std::vector's in R.

abseil — by Xingchi Li, 2 years ago

'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>.

sanic — by Nikolas Kuschnig, 2 years ago

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.

chicane — by Syed Haider, 4 years ago

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.

dlib — by Jan Wijffels, 5 years ago

Allow Access to the 'Dlib' C++ Library

Interface for 'Rcpp' users to 'dlib' < http://dlib.net> which is a 'C++' toolkit containing machine learning algorithms and computer vision tools. It is used in a wide range of domains including robotics, embedded devices, mobile phones, and large high performance computing environments. This package allows R users to use 'dlib' through 'Rcpp'.

cladoRcpp — by Nicholas J. Matzke, 7 years ago

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.