The GPLv2 of Rcpp and the Apache 2.0 of the oneTBB compiled with Stan are incompatible when bundled together as a single binary, which is why these scripts are being provided as a buildable R package on GitHub but not as a precompiled binary ready for installation.

See: https://github.com/stan-dev/stan/wiki/Stan-Licensing

Rcpp

by: Dirk Eddelbuettel, Romain Francois, JJ Allaire, Kevin Ushey, Qiang Kou, Nathan Russell, Iñaki Ucar, Doug Bates, and John Chambers

https://cran.r-project.org/web/packages/Rcpp/index.html
https://github.com/RcppCore/Rcpp/tree/master

GNU General Public License v2.0
https://github.com/RcppCore/Rcpp/blob/master/LICENSE
https://github.com/RcppCore/Rcpp/blob/0905d92e0046de5f171d4fde752d97e8733738be/LICENSE

Stan Math

Bob Carpenter
https://bob-carpenter.github.io/

https://mc-stan.org/math/
https://github.com/stan-dev/math

BSD 3-Clause License

The Stan Math Library depends on the Intel TBB library which is licensed under the Apache 2.0 license. This dependency implies an additional restriction as compared to the new BSD license alone. The Apache 2.0 license is incompatible with GPL-2 licensed code if distributed as a unitary binary. You may refer to the Licensing page on the Stan wiki.

Boost / BH

https://www.boost.org/
https://github.com/boostorg

Boost license 1.0
https://www.boost.org/LICENSE_1_0.txt
https://github.com/boostorg/boost/blob/master/LICENSE_1_0.txt

“Boost Software License - Version 1.0 - August 17th, 2003

Permission is hereby granted, free of charge, to any person or organization obtaining a copy of the software and accompanying documentation covered by this license (the “Software”) to use, reproduce, display, distribute, execute, and transmit the Software, and to prepare derivative works of the Software, and to permit third-parties to whom the Software is furnished to do so, all subject to the following:

The copyright notices in the Software and this entire statement, including the above license grant, this restriction and the following disclaimer, must be included in all copies of the Software, in whole or in part, and all derivative works of the Software, unless such copies or derivative works are solely in the form of machine-executable object code generated by a source language processor.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, TITLE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR ANYONE DISTRIBUTING THE SOFTWARE BE LIABLE FOR ANY DAMAGES OR OTHER LIABILITY, WHETHER IN CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.”

Eigen

The Eigen project was started by Benoît Jacob (founder) and Gaël Guennebaud (guru). Many other people have since contributed their talents to help make Eigen successful.

https://eigen.tuxfamily.org/
https://gitlab.com/libeigen/eigen

MPL2 (Mozilla Public License)
https://www.mozilla.org/en-US/MPL/2.0/FAQ/

SUNDIALS

Lawrence Livermore National Security and Southern Methodist University.

https://computing.llnl.gov/projects/sundials

oneTBB

Unified Acceleration (UXL) Foundation

https://github.com/uxlfoundation/oneTBB

Apache 2.0
https://github.com/uxlfoundation/oneTBB/blob/master/LICENSE.txt

nlopt

Steven G. Johnson
The NLopt nonlinear-optimization package

http://github.com/stevengj/nlopt
https://nlopt.readthedocs.io/en/latest/

GNU Lesser General Public License (LGPL)
https://nlopt.readthedocs.io/en/latest/NLopt_License_and_Copyright/

pcg

Melissa E. O’Neill
https://www.cs.hmc.edu/~oneill/index.html

https://www.pcg-random.org/
https://github.com/imneme/pcg-cpp

Apache 2.0 and The MIT License

unistd.h, part of the C POSIX library

The IEEE and The Open Group
https://pubs.opengroup.org/onlinepubs/9799919799/
https://www.opengroup.org/membership/forums/platform/unix

https://pubs.opengroup.org/onlinepubs/7908799/xsh/unistd.h.html

Available and licensed on your local system

dtwclust

Alexis Sarda-Espinosa
Sarda-Espinosa A (2024). dtwclust: Time Series Clustering Along with Optimizations for the Dynamic Time Warping Distance. R package version 6.0.0

Specifically using DTW Barycenter Averaging, from:
Petitjean F, Ketterlin A and Gancarski P (2011). “A global averaging method for dynamic time warping, with applications to clustering.” Pattern Recognition, 44(3), pp. 678 - 693. ISSN 0031-3203, doi:10.1016/j.patcog.2010.09.013, https://www.sciencedirect.com/science/article/pii/S003132031000453X

https://cran.r-project.org/package=dtwclust
https://github.com/asardaes/dtwclust

GPLv3

ggplot2

by: ggplot2 core developer team

https://ggplot2.tidyverse.org/

The MIT license
https://github.com/tidyverse/ggplot2

Dependency licenses