Quasi-Monte Carlo Methods in Python

Quasi-Monte Carlo Methods in Python - Published in JOSS (2023)

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Owner

JOSS Publication

Quasi-Monte Carlo Methods in Python

Published

April 23, 2023

DOI

10.21105/joss.05309

Volume 8, Issue 84, Page 5309

Authors

Pamphile T. Roy
Quansight

Art B. Owen
Stanford University

Maximilian Balandat
Meta

Matt Haberland
California Polytechnic State University, San Luis Obispo, USA

Editor

Mehmet Hakan Satman

Tags

SciPy statistics Quasi-Monte Carlo methods

View PDF Review Thread Software Archive

Citation (CITATION.bib)

@ARTICLE{2020SciPy-NMeth,
  author  = {Virtanen, Pauli and Gommers, Ralf and Oliphant, Travis E. and
            Haberland, Matt and Reddy, Tyler and Cournapeau, David and
            Burovski, Evgeni and Peterson, Pearu and Weckesser, Warren and
            Bright, Jonathan and {van der Walt}, St{\'e}fan J. and
            Brett, Matthew and Wilson, Joshua and Millman, K. Jarrod and
            Mayorov, Nikolay and Nelson, Andrew R. J. and Jones, Eric and
            Kern, Robert and Larson, Eric and Carey, C J and
            Polat, {\.I}lhan and Feng, Yu and Moore, Eric W. and
            {VanderPlas}, Jake and Laxalde, Denis and Perktold, Josef and
            Cimrman, Robert and Henriksen, Ian and Quintero, E. A. and
            Harris, Charles R. and Archibald, Anne M. and
            Ribeiro, Ant{\^o}nio H. and Pedregosa, Fabian and
            {van Mulbregt}, Paul and {SciPy 1.0 Contributors}},
  title   = {{{SciPy} 1.0: Fundamental Algorithms for Scientific
            Computing in Python}},
  journal = {Nature Methods},
  year    = {2020},
  volume  = {17},
  pages   = {261--272},
  url     = {https://doi.org/10.1038/s41592-019-0686-2},
  adsurl  = {https://ui.adsabs.harvard.edu/abs/2020NatMe..17..261V},
  doi     = {10.1038/s41592-019-0686-2},
}

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