R access to the Sequential Monte Carlo Template Classes
 by Johansen <doi:10.18637/jss.v030.i06> is provided. At present, four
 additional examples have been added, and the first example from the JSS
 paper has been extended. Further integration and extensions are planned.

The mature and widely-used C++ logging library 'spdlog' by Gabi Melman provides
 many desirable features. This package bundles these header files for easy use by R packages
 from both their R and C or C++ code. Explicit use via 'LinkingTo:' is also supported. Also
 see the 'spdl' package which enhanced this package with a consistent R and C++ interface.

The 'Streamulus' (template, header-only) library by
 Irit Katriel (at <https://github.com/iritkatriel/streamulus>)
 provides a very powerful yet convenient framework for stream
 processing. This package connects 'Streamulus' to R by providing 
 both the header files and all examples.

Provides a C++11-style thread class and thread pool that can safely
    be interrupted from R. See Nagler (2021) <doi:10.18637/jss.v097.c01>.

Provides 'Rcpp' bindings for 'cpptimer', a simple tic-toc timer class for benchmarking 'C++' code <https://github.com/BerriJ/cpptimer>. It's not just simple, it's blazing fast! This sleek tic-toc timer class supports overlapping timers as well as 'OpenMP' parallelism <https://www.openmp.org/>. It boasts a microsecond-level time resolution. We did not find any overhead of the timer itself at this resolution. Results (with summary statistics) are automatically passed back to 'R' as a data frame.

R-level and C++-level functionality
    to generate random deviates from and calculate moments of a
    Truncated Normal distribution using the algorithm of Robert (1995) <DOI:10.1007/BF00143942>.
    In addition to RNG, functions for calculating moments, densities,
    and entropies are provided at both levels.

The configuration format defined by 'TOML' (which expands to
 "Tom's Obvious Markup Language") specifies an excellent format
 (described at <https://toml.io/en/>) suitable for both human editing
 as well as the common uses of a machine-readable format. This package
 uses 'Rcpp' to connect to the 'toml++' parser written by Mark Gillard
 to R.