Fast Resampling and Monte Carlo Methods in Python

Fast Resampling and Monte Carlo Methods in Python - Published in JOSS (2023)

https://github.com/mdhaber/scipy

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SciPy (pronounced "Sigh Pie") is an open-source software for mathematics,
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Owner

JOSS Publication

`tukey_hsd`: An Accurate Implementation of the Tukey Honestly Significant Difference Test in Python

Published

July 05, 2022

DOI

10.21105/joss.04383

Volume 7, Issue 75, Page 4383

Authors

Dominic Chmiel
California Polytechnic State University, San Luis Obispo, USA

Samuel Wallan
California Polytechnic State University, San Luis Obispo, USA

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

Editor

Mikkel Meyer Andersen

Tags

SciPy statistics hypothesis testing statistical distributions

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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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