Draft:ParaMonte

ParaMonte
Original author(s)	The Computational Data Science Lab
Initial release	June 1, 2012
Stable release	1.5.1 / Jan 1, 2021
Written in	C, C++, Fortran, MATLAB, Python
Operating system	Unix-like, Microsoft Windows, Mac OS X
Platform	Intel x86 - 32-bit, x64, Aarch64
Type	Statistical package
License	MIT license
Website	cdslab.org/paramonte, github.com/cdslaborg/paramonte

Submission declined on 5 July 2024 by SafariScribe (talk).

This submission is not adequately supported by reliable sources. Reliable sources are required so that information can be verified. If you need help with referencing, please see Referencing for beginners and Citing sources.

This draft's references do not show that the subject qualifies for a Wikipedia article. In summary, the draft needs multiple published sources that are:

in-depth (not just passing mentions about the subject)
reliable
secondary
independent of the subject

Make sure you add references that meet these criteria before resubmitting. Learn about mistakes to avoid when addressing this issue. If no additional references exist, the subject is not suitable for Wikipedia.

If you would like to continue working on the submission, click on the "Edit" tab at the top of the window.
If you have not resolved the issues listed above, your draft will be declined again and potentially deleted.
If you need extra help, please ask us a question at the AfC Help Desk or get live help from experienced editors.
Please do not remove reviewer comments or this notice until the submission is accepted.

Where to get help

If you need help editing or submitting your draft, please ask us a question at the AfC Help Desk or get live help from experienced editors. These venues are only for help with editing and the submission process, not to get reviews.
If you need feedback on your draft, or if the review is taking a lot of time, you can try asking for help on the talk page of a relevant WikiProject. Some WikiProjects are more active than others so a speedy reply is not guaranteed.

How to improve a draft

Wikipedia:Contributing to Wikipedia – a basic overview on how to edit Wikipedia.
Help:Wikitext – how to use the markup
Help:Referencing for beginners – how to include references
Wikipedia:Article development – how to develop your article
Wikipedia:Writing better articles – how to improve your article
Wikipedia:Verifiability – make sure your article includes reliable third-party sources

You can also browse Wikipedia:Featured articles and Wikipedia:Good articles to find examples of Wikipedia's best writing on topics similar to your proposed article.

Improving your odds of a speedy review

To improve your odds of a faster review, tag your draft with relevant WikiProject tags using the button below. This will let reviewers know a new draft has been submitted in their area of interest. For instance, if you wrote about a female astronomer, you would want to add the Biography, Astronomy, and Women scientists tags.

Add tags to your draft

Editor resources

Easy tools: Citation bot (help) | Advanced: Fix bare URLs

Declined by SafariScribe 4 months ago. Last edited by Citation bot 4 months ago. Reviewer: Inform author.

Resubmit

Please note that if the issues are not fixed, the draft will be declined again.

ParaMonte^[1] (standing for Parallel Monte Carlo) is an open-source, permissively-licensed (e.g., MIT License), serial and MPI / OpenMP / Coarray-parallelized library of Monte Carlo and Machine Learning algorithms for mathematical optimization, statistical sampling (e.g., Markov Chain Monte Carlo (MCMC)), and deterministic and stochastic numerical integration of mathematical density functions of arbitrary dimensions, in particular, the posterior distributions of Bayesian models in data science, machine learning, and scientific inference^[2]. The library is written in a mixture of programming languages, primarily consisting of modern Fortran, C, C++, MATLAB, Python^[3].

The ParaMonte Fortran library contains nearly 1 million lines^[4] of fully generic multi-precision interfaces and routines for various Monte Carlo integration and machine learning tasks (e.g., cluster analysis^[5]) written in Fortran-2008. The Fortran version of the library also contains fully modernized, generic, multi-precision implementations and significant extensions of the FFTPACK^[6] for Fast Fourier Transform^[7] and QUADPACK^[8] for integration using Adaptive Quadrature methods^[9].

The MATLAB^[10] and Python^[11] versions of the library are available through MathWorks MATLAB Central FileExchange^[12] and Python Package Index^[13], respectively. The library is released with many examples^[14] and usage instructions^[15] for different programming languages and is fully documented for all supported programming languages (e.g., C^[16], C++^[17], Fortran^[18], MATLAB^[19]).

References

^ "Cdslaborg/Paramonte". GitHub.
^ Shahmoradi, Amir; Bagheri, Fatemeh (2021). "ParaMonte: A high-performance serial/Parallel Monte Carlo simulation library for C, C++, Fortran". Journal of Open Source Software. 6 (61): 2741. arXiv:2009.14229. Bibcode:2021JOSS....6.2741S. doi:10.21105/joss.02741.
^ Shahmoradi, Amir; Bagheri, Fatemeh (2020). "ParaDRAM: A Cross-Language Toolbox for Parallel High-Performance Delayed-Rejection Adaptive Metropolis Markov Chain Monte Carlo Simulations". arXiv:2008.09589 [cs.CE].
^ "Count LOC online".
^ "ParaMonte Fortran 2.0.0: Pm_clustering Module Reference".
^ Rodrigue, G. (1982). Parallel computations. Academic Press. ISBN 978-0-12-592101-5.
^ "ParaMonte Fortran 2.0.0: Pm_fftpack Module Reference".
^ Quadpack: A Subroutine Package for Automatic Integration. Springer. 6 December 2012. ISBN 978-3-642-61786-7.
^ "ParaMonte Fortran 2.0.0: Pm_quadPack Module Reference".
^ Kumbhare, Shashank; Shahmoradi, Amir (2020). "MatDRAM: A pure-MATLAB Delayed-Rejection Adaptive Metropolis-Hastings Markov Chain Monte Carlo Sampler". arXiv:2010.04190 [physics.data-an].
^ Shahmoradi, Amir; Bagheri, Fatemeh; Joshua Alexander Osborne (2020). "Fast fully-reproducible serial/Parallel Monte Carlo and MCMC simulations and visualizations via ParaMonte::Python library". arXiv:2010.00724 [cs.MS].
^ "ParaMonte - File Exchange - MATLAB Central".
^ "Paramonte: Plain Powerful Parallel Monte Carlo and adaptive MCMC Library".
^ "Cdslaborg/Paramontex". GitHub.
^ "| ParaMonte: Parallel Monte Carlo Library".
^ "ParaMonte C 2.0.0: ParaMonte C 2.0.0".
^ "ParaMonte C++ 2.0.0: ParaMonte C++ 2.0.0".
^ "ParaMonte Fortran 2.0.0: ParaMonte Fortran 2.0.0".
^ "ParaMonte MATLAB 3.0.0: ParaMonte MATLAB 3.0.0".

External links

Category:Computational statistics Category:Free Bayesian statistics software Category:Monte Carlo software Category:Numerical programming languages Category:Domain-specific programming languages Category:Probabilistic software

[1] "Cdslaborg/Paramonte". GitHub.

[2] Shahmoradi, Amir; Bagheri, Fatemeh (2021). "ParaMonte: A high-performance serial/Parallel Monte Carlo simulation library for C, C++, Fortran". Journal of Open Source Software. 6 (61): 2741. arXiv:2009.14229. Bibcode:2021JOSS....6.2741S. doi:10.21105/joss.02741.

[3] Shahmoradi, Amir; Bagheri, Fatemeh (2020). "ParaDRAM: A Cross-Language Toolbox for Parallel High-Performance Delayed-Rejection Adaptive Metropolis Markov Chain Monte Carlo Simulations". arXiv:2008.09589 [cs.CE].

[4] "Count LOC online".

[5] "ParaMonte Fortran 2.0.0: Pm_clustering Module Reference".

[6] Rodrigue, G. (1982). Parallel computations. Academic Press. ISBN 978-0-12-592101-5.

[7] "ParaMonte Fortran 2.0.0: Pm_fftpack Module Reference".

[8] Quadpack: A Subroutine Package for Automatic Integration. Springer. 6 December 2012. ISBN 978-3-642-61786-7.

[9] "ParaMonte Fortran 2.0.0: Pm_quadPack Module Reference".

[10] Kumbhare, Shashank; Shahmoradi, Amir (2020). "MatDRAM: A pure-MATLAB Delayed-Rejection Adaptive Metropolis-Hastings Markov Chain Monte Carlo Sampler". arXiv:2010.04190 [physics.data-an].

[11] Shahmoradi, Amir; Bagheri, Fatemeh; Joshua Alexander Osborne (2020). "Fast fully-reproducible serial/Parallel Monte Carlo and MCMC simulations and visualizations via ParaMonte::Python library". arXiv:2010.00724 [cs.MS].

[12] "ParaMonte - File Exchange - MATLAB Central".

[13] "Paramonte: Plain Powerful Parallel Monte Carlo and adaptive MCMC Library".

[14] "Cdslaborg/Paramontex". GitHub.

[15] "| ParaMonte: Parallel Monte Carlo Library".

[16] "ParaMonte C 2.0.0: ParaMonte C 2.0.0".

[17] "ParaMonte C++ 2.0.0: ParaMonte C++ 2.0.0".

[18] "ParaMonte Fortran 2.0.0: ParaMonte Fortran 2.0.0".

[19] "ParaMonte MATLAB 3.0.0: ParaMonte MATLAB 3.0.0".

[1]

[2]

[3]

[4]

[5]

[6]

[7]

[8]

[9]

[10]

[11]

[12]

[13]

[14]

[15]

[16]

[17]

[18]

[19]

See also

References

External links