Global Optimization by Differential Evolution in C++

An efficient C++ based implementation of the 'DEoptim' function which performs global optimization by differential evolution. Its creation was motivated by trying to see if the old approximation "easier, shorter, faster: pick any two" could in fact be extended to achieving all three goals while moving the code from plain old C to modern C++. The initial version did in fact do so, but a good part of the gain was due to an implicit code review which eliminated a few inefficiencies which have since been eliminated in 'DEoptim'.

"Cereal Headers for R and C++ Serialization"

To facilitate using 'cereal' with R via 'cpp11' or 'Rcpp'. 'cereal' is a header-only C++11 serialization library. 'cereal' takes arbitrary data types and reversibly turns them into different representations, such as compact binary encodings, 'XML', or 'JSON'. 'cereal' was designed to be fast, light-weight, and easy to extend - it has no external dependencies and can be easily bundled with other code or used standalone. Please see < https://uscilab.github.io/cereal/> for more information.

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.

R Interface to Google RE2 (C++) Regular Expression Library

Pattern matching, extraction, replacement and other string processing operations using Google's RE2 < https://github.com/google/re2> regular-expression engine. Consistent interface (similar to 'stringr'). RE2 uses finite-automata based techniques, and offers a fast and safe alternative to backtracking regular-expression engines like those used in 'stringr', 'stringi' and other PCRE implementations.

'Rcpp' Integration for the 'Armadillo' Templated Linear Algebra Library

'Armadillo' is a templated C++ linear algebra library aiming towards a good balance between speed and ease of use. It provides high-level syntax and functionality deliberately similar to Matlab. It is useful for algorithm development directly in C++, or quick conversion of research code into production environments. It provides efficient classes for vectors, matrices and cubes where dense and sparse matrices are supported. Integer, floating point and complex numbers are supported. A sophisticated expression evaluator (based on template meta-programming) automatically combines several operations to increase speed and efficiency. Dynamic evaluation automatically chooses optimal code paths based on detected matrix structures. Matrix decompositions are provided through integration with LAPACK, or one of its high performance drop-in replacements (such as 'MKL' or 'OpenBLAS'). It can automatically use 'OpenMP' multi-threading (parallelisation) to speed up computationally expensive operations. The 'RcppArmadillo' package includes the header files from the 'Armadillo' library; users do not need to install 'Armadillo' itself in order to use 'RcppArmadillo'. Starting from release 15.0.0, the minimum compilation standard is C++14 so 'Armadillo' version 14.6.3 is included as a fallback when an R package forces the C++11 standard. Package authors should set a '#define' to select the 'current' version, or select the 'legacy' version (also chosen as default) if they must. See 'GitHub issue #475' for details. Since release 7.800.0, 'Armadillo' is licensed under Apache License 2; previous releases were under licensed as MPL 2.0 from version 3.800.0 onwards and LGPL-3 prior to that; 'RcppArmadillo' (the 'Rcpp' bindings/bridge to Armadillo) is licensed under the GNU GPL version 2 or later, as is the rest of 'Rcpp'.

Automated C Code Generation for 'deSolve', 'bvpSolve'

Generates all necessary C functions allowing the user to work with the compiled-code interface of ode() and bvptwp(). The implementation supports "forcings" and "events". Also provides functions to symbolically compute Jacobians, sensitivity equations and adjoint sensitivities being the basis for sensitivity analysis.

Handle Missing Tensor Data with C++ Integration

To handle higher-order tensor data. See Kolda and Bader (2009) for details on tensor. While existing packages on tensor data extend the base 'array' class to some data classes, this package serves as an alternative resort to handle tensor only as 'array' class. Some functionalities related to missingness are also supported.

Interface to 'Lp_solve' v. 5.5 to Solve Linear/Integer Programs

Lp_solve is freely available (under LGPL 2) software for solving linear, integer and mixed integer programs. In this implementation we supply a "wrapper" function in C and some R functions that solve general linear/integer problems, assignment problems, and transportation problems. This version calls lp_solve version 5.5.

Check 'C' and 'C++' Files using 'Cppcheck'

Allow to run 'Cppcheck' (< https://cppcheck.sourceforge.io/>) on 'C' and 'C++' files with a 'R' command or a 'RStudio' addin. The report appears in the 'RStudio' viewer pane as a formatted 'HTML' file. It is also possible to get this report with a 'shiny' application. 'Cppcheck' can spot many error types and it can also give some recommendations on the 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) .