R and C++11

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

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.

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) .

'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.

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.

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) .

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) .

C-Statistics for Risk Prediction Models with Censored Survival Data

Performs inference for C of risk prediction models with censored survival data, using the method proposed by Uno et al. (2011) . Inference for the difference in C between two competing prediction models is also implemented.

Multiple Precision Arithmetic

Multiple Precision Arithmetic (big integers and rationals, prime number tests, matrix computation), "arithmetic without limitations" using the C library GMP (GNU Multiple Precision Arithmetic).

C/C++ Source Code to Trigger Address and Undefined Behaviour Sanitizers

Recent gcc and clang compiler versions provide functionality to test for memory violations and other undefined behaviour; this is often referred to as "Address Sanitizer" (or 'ASAN') and "Undefined Behaviour Sanitizer" ('UBSAN'). The Writing R Extension manual describes this in some detail in Section 4.3 title "Checking Memory Access". This feature has to be enabled in the corresponding binary, eg in R, which is somewhat involved as it also required a current compiler toolchain which is not yet widely available, or in the case of Windows, not available at all (via the common Rtools mechanism). As an alternative, pre-built Docker containers such as the Rocker container 'r-devel-san' or the multi-purpose container 'r-debug' can be used. This package then provides a means of testing the compiler setup as the known code failures provides in the sample code here should be detected correctly, whereas a default build of R will let the package pass. The code samples are based on the examples from the Address Sanitizer Wiki at < https://github.com/google/sanitizers/wiki>.