System for Building and Debugging C/C++ Dynamic Libraries

A build system based on 'GNU make' that creates and maintains (simply) make files in an R session and provides GUI debugging support through 'Microsoft Visual Code'.

Approximate String Matching, Fuzzy Text Search, and String Distance Functions

Implements an approximate string matching version of R's native 'match' function. Also offers fuzzy text search based on various string distance measures. Can calculate various string distances based on edits (Damerau-Levenshtein, Hamming, Levenshtein, optimal sting alignment), qgrams (q- gram, cosine, jaccard distance) or heuristic metrics (Jaro, Jaro-Winkler). An implementation of soundex is provided as well. Distances can be computed between character vectors while taking proper care of encoding or between integer vectors representing generic sequences. This package is built for speed and runs in parallel by using 'openMP'. An API for C or C++ is exposed as well. Reference: MPJ van der Loo (2014) .

'2bit' 'C' Library

A trimmed down copy of the "kent-core source tree" turned into a 'C' library for manipulation of '.2bit' files. See < https://genome.ucsc.edu/FAQ/FAQformat.html#format7> for a quick overview of the '2bit' format. The "kent-core source tree" can be found here: < https://github.com/ucscGenomeBrowser/kent-core/>. Only the '.c' and '.h' files from the source tree that are related to manipulation of '.2bit' files were kept. Note that the package is primarily useful to developers of other R packages who wish to use the '2bit' 'C' library in their own 'C'/'C++' code.

Sparse Matrix C++ Classes Including Sparse Cholesky LDL Decomposition of Symmetric Matrices

'C++' classes for sparse matrix methods including implementation of sparse LDL decomposition of symmetric matrices and solvers described by Timothy A. Davis (2016) < https://fossies.org/linux/SuiteSparse/LDL/Doc/ldl_userguide.pdf>. Provides a set of C++ classes for basic sparse matrix specification and linear algebra, and a class to implement sparse LDL decomposition and solvers. See < https://github.com/samuel-watson/SparseChol> for details.

R and C++11

Rcpp11 includes a header only C++11 library that facilitates integration between R and modern C++.

'Rcpp'-Based Helper Functions to Pass 'Int64' and 'nanotime' Values Between 'R' and 'C++'

'Int64' values can be created and accessed via the 'bit64' package and its 'integer64' class which package the 'int64' representation cleverly into a 'double'. The 'nanotime' packages builds on this to support nanosecond-resolution timestamps. This packages helps conversions between 'R' and 'C++' via several helper functions provided via a single header file. A complete example client package is included as an illustration.

RUV-III-C

Variations of Remove Unwanted Variation-III (RUV-III) known as RUV-III-C (RUV-III Complete). RUV-III performs normalisation using negative control variables and replication. RUV-III-C extends this method to cases where the data contains missing values, by applying RUV-III to complete subsets of the data. Originally designed for SWATH-MS proteomics datasets. Poulos et al. (2020) .

Interpolation From C

Simple interpolation methods designed to be used from C code. Supports constant, linear and spline interpolation. An R wrapper is included but this package is primarily designed to be used from C code using 'LinkingTo'. The spline calculations are classical cubic interpolation, e.g., Forsythe, Malcolm and Moler (1977) .

Solvers for Initial Value Problems of Differential Equations ('ODE', 'DAE', 'DDE')

Functions that solve initial value problems of a system of first-order ordinary differential equations ('ODE'), of partial differential equations ('PDE'), of differential algebraic equations ('DAE'), and of delay differential equations. The functions provide an interface to the FORTRAN functions 'lsoda', 'lsodar', 'lsode', 'lsodes' of the 'ODEPACK' collection, to the FORTRAN functions 'dvode', 'zvode' and 'daspk' and a C-implementation of solvers of the 'Runge-Kutta' family with fixed or variable time steps. The package contains routines designed for solving 'ODEs' resulting from 1-D, 2-D and 3-D partial differential equations ('PDE') that have been converted to 'ODEs' by numerical differencing.

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) for details.