A collection of open source libraries for numerical computing
    (numerical integration, optimization, etc.) and their integration with
    'Rcpp'.

High level functions for parallel programming with 'Rcpp'.
    For example, the 'parallelFor()' function can be used to convert the work of
    a standard serial "for" loop into a parallel one and the 'parallelReduce()'
    function can be used for accumulating aggregate or other values.

'Rcpp' bindings for 'PLANC', a highly parallel
             and extensible NMF/NTF  (Non-negative Matrix/Tensor Factorization) library.
             Wraps algorithms described in
             Kannan et. al (2018) <doi:10.1109/TKDE.2017.2767592> and
             Eswar et. al (2021) <doi:10.1145/3432185>.
             Implements algorithms described in
             Welch et al. (2019) <doi:10.1016/j.cell.2019.05.006>,
             Gao et al. (2021) <doi:10.1038/s41587-021-00867-x>, and
             Kriebel & Welch (2022) <doi:10.1038/s41467-022-28431-4>.

Allows to display a progress bar in the R
    console for long running computations taking place in c++ code,
    and support for interrupting those computations even in multithreaded
    code, typically using OpenMP.

'QuantLib' bindings are provided for R using 'Rcpp' via an updated
 variant of the header-only 'Quantuccia' project (put together initially by Peter
 Caspers) offering an essential subset of 'QuantLib' (and now maintained separately
 for the calendaring subset). See the included file 'AUTHORS' for a full list of
 contributors to both 'QuantLib' and 'Quantuccia'.

Connection to the 'Redis' (or 'Valkey') key/value store
 using the C-language client library 'hiredis' (included as a fallback)
 with 'MsgPack' encoding provided via 'RcppMsgPack' headers. It now
 also includes the pub/sub functions from the 'rredis' package.

Provides fast and efficient routines for
    common rolling / windowed operations. Routines for the
    efficient computation of windowed mean, median,
    sum, product, minimum, maximum, standard deviation
    and variance are provided.