74:
683:
Brauner, Jan M.; Mindermann, Sören; Sharma, Mrinank; Johnston, David; Salvatier, John; Gavenčiak, Tom; Stephenson, Anna B.; Leech, Gavin; Altman, George; Mikulik, Vladimir; Norman, Alexander John; Monrad, Joshua
Teperowski; Besiroglu, Tamay; Ge, Hong; Hartwick, Meghan A.; Teh, Yee Whye;
396:
Abril-Pla O, Andreani V, Carroll C, Dong L, Fonnesbeck CJ, Kochurov M, Kumar R, Lao J, Luhmann CC, Martin OA, Osthege M, Vieira R, Wiecki T, Zinkov R. (2023) PyMC: a modern, and comprehensive probabilistic programming framework in Python. PeerJ Comput. Sci. 9:e1516
215:
extensions for performing computations, PyMC relies on PyTensor, a Python library that allows defining, optimizing, and efficiently evaluating mathematical expressions involving multi-dimensional arrays. From version 3.8 PyMC relies on
993:
Wang, Yan; Huang, Hong; Huang, Lida; Ristic, Branko (2017). "Evaluation of
Bayesian source estimation methods with Prairie Grass observations and Gaussian plume model: A comparison of likelihood functions and distance measures".
210:
PyMC performs inference based on advanced Markov chain Monte Carlo and/or variational fitting algorithms. It is a rewrite from scratch of the previous version of the PyMC software. Unlike PyMC2, which had used
2253:
1283:
Gething, Peter W.; Elyazar, Iqbal R. F.; Moyes, Catherine L.; Smith, David L.; Battle, Katherine E.; Guerra, Carlos A.; Patil, Anand P.; Tatem, Andrew J.; Howes, Rosalind E. (2012-09-06).
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Bradbury, James; Frostig, Roy; Hawkins, Peter; James, Matthew James; Leary, Chris; Maclaurin, Dougal; Necula, George; Paszke, Adam; VanderPlas, Jake; Wanderman-Milne, Skye; Zhang, Qiao.
1124:
Graham, Nicholas A. J.; Jennings, Simon; MacNeil, M. Aaron; Mouillot, David; Wilson, Shaun K. (2015). "Predicting climate-driven regime shifts versus rebound potential in coral reefs".
761:
Wagner, Stacey D.; Struck, Adam J.; Gupta, Riti; Farnsworth, Dylan R.; Mahady, Amy E.; Eichinger, Katy; Thornton, Charles A.; Wang, Eric T.; Berglund, J. Andrew (2016-09-28).
1689:
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936:"Detection of methylation, acetylation and glycosylation of protein residues by monitoring13C chemical-shift changes: A quantum-chemical study"
1029:
MacNeil, M. Aaron; Chong-Seng, Karen M.; Pratchett, Deborah J.; Thompson, Casssandra A.; Messmer, Vanessa; Pratchett, Morgan S. (2017-03-14).
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Cavanagh, James F; Wiecki, Thomas V; Cohen, Michael X; Figueroa, Christina M; Samanta, Johan; Sherman, Scott J; Frank, Michael J (2011).
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were added. The PyMC team has released the revised computational backend under the name PyTensor and continues the development of PyMC.
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is a Python library for defining, optimizing, and efficiently evaluating mathematical expressions involving multi-dimensional arrays.
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Salvatier J, Wiecki TV, Fonnesbeck C. (2016) Probabilistic programming in Python using PyMC3. PeerJ Computer
Science 2:e55
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251:, ecology and psychology. Previous versions of PyMC were also used widely, for example in climate science, public health,
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1177:"National, Regional, and Global Trends in Infertility Prevalence Since 1990: A Systematic Analysis of 277 Health Surveys"
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Sharma, Amit; Johansson, Linda; Dunevall, Elin; Wahlgren, Weixiao Y.; Neutze, Richard; Katona, Gergely (2017-03-01).
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763:"Dose-Dependent Regulation of Alternative Splicing by MBNL Proteins Reveals Biomarkers for Myotonic Dystrophy"
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Theano under the name Aesara. Large parts of the Theano codebase have been refactored and compilation through
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Mascarenhas, Maya N.; Flaxman, Seth R.; Boerma, Ties; Vanderpoel, Sheryl; Stevens, Gretchen A. (2012-12-18).
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Kucukelbir, Alp; Ranganath, Rajesh; Blei, David M. (June 2015). "Automatic
Variational Inference in Stan".
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1067:"Peripheral Visual Cues: Their Fate in Processing and Effects on Attention and Temporal-Order Perception"
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879:"Estimating the difference between structure-factor amplitudes using multivariate Bayesian inference"
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PyMC has been used to solve inference problems in several scientific domains, including
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Bayesian
Analysis with Python : A Practical Guide to Probabilistic Modeling
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is a probabilistic programming language for statistical inference written in C++
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Bayesian
Methods for Hackers: Probabilistic Programming and Bayesian Inference
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announced plans to discontinue development in 2017, the PyMC team evaluated
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Hilbe, Joseph M.; Souza, Rafael S. de; Ishida, Emille E. O. (2017-04-30).
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1285:"A Long Neglected World Malaria Map: Plasmodium vivax Endemicity in 2010"
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Katona, Gergely; Garcia-Bonete, Maria-Jose; Lundholm, Ida (2016-05-01).
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290:(MCMC) algorithms for Bayesian inference and stochastic, gradient-based
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Bayesian Models for
Astrophysical Data: Using R, JAGS, Python, and Stan
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project, developed by the community and has been fiscally sponsored by
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to handle plotting, diagnostics, and statistical checks. PyMC and
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is a high-level
Bayesian model-building interface based on PyMC
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Chindelevitch, Leonid; Gal, Yarin; Kulveit, Jan (2020-12-15).
589:
Greiner, J.; Burgess, J. M.; Savchenko, V.; Yu, H.-F. (2016).
352:
a Python library for exploratory analysis of
Bayesian models
1454:"The Future of PyMC3, or: Theano is Dead, Long Live Theano"
566:"NumFOCUS Announces New Fiscally Sponsored Project: PyMC3"
183:
822:"Asymmetry in serial femtosecond crystallography data"
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PyMC implements non-gradient-based and gradient-based
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Martin, Osvaldo; Kumar, Ravin; Lao, Junpeng (2021).
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305:and PyMC's default engine for continuous variables
546:"The Algorithms Behind Probabilistic Programming"
735:Systrom, Kevin; Vladek, Thomas; Krieger, Mike.
311:, PyMC's default engine for discrete variables
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591:"On the Fermi-GBM Event 0.4 s after GW150914"
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314:Sequential Monte Carlo for static posteriors
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1430:"Theano, TensorFlow and the Future of PyMC"
467:Bayesian Modeling and Computation in Python
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498:Davidson-Pilon, Cameron (2015-09-30).
247:, molecular biology, crystallography,
1401:Lamblin, Pascal (28 September 2017).
570:NumFOCUS | Open Code = Better Science
7:
1539:Journal of Machine Learning Research
294:for approximate Bayesian inference.
201:probabilistic programming language
27:Probabilistic programming language
25:
2234:Free Bayesian statistics software
595:The Astrophysical Journal Letters
103:https://github.com/pymc-devs/pymc
1289:PLOS Neglected Tropical Diseases
883:Acta Crystallographica Section A
826:Acta Crystallographica Section A
319:approximate Bayesian computation
2244:Numerical programming languages
1428:Developers, PyMC (2018-05-17).
1403:"MILA and the future of Theano"
504:. Addison-Wesley Professional.
331:Black-box Variational Inference
199:(formerly known as PyMC3) is a
1016:10.1016/j.atmosenv.2017.01.014
662:. Cambridge University Press.
1:
470:. CRC-press. pp. 1–420.
433:Bayesian Analysis with Python
1302:10.1371/journal.pntd.0001814
1194:10.1371/journal.pmed.1001356
780:10.1371/journal.pgen.1006316
292:variational Bayesian methods
737:"Rt.live Github repository"
626:10.3847/2041-8205/827/2/L38
317:Sequential Monte Carlo for
173:Apache License, Version 2.0
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2194:
1622:(Third ed.). Packt.
895:10.1107/S2053273316003430
838:10.1107/s2053273316018696
226:probabilistic programming
224:are the two most popular
92:
60:
2229:Computational statistics
2042:World Programming System
1618:Martin, Osvaldo (2024).
1084:10.3389/fpsyg.2016.01442
436:. Packt Publishing Ltd.
430:Martin, Osvaldo (2024).
288:Markov chain Monte Carlo
1348:Parasites & Vectors
1071:Frontiers in Psychology
996:Atmospheric Environment
703:10.1126/science.abd9338
303:Hamiltonian Monte Carlo
298:MCMC-based algorithms:
2249:Probabilistic software
1596:Cite journal requires
1361:10.1186/1756-3305-7-37
264:TensorFlow Probability
79:; 2 months ago
1655:repository hosted on
403:10.7717/peerj-cs.1516
326:Variational inference
49:May 4, 2013
41:PyMC Development Team
2239:Monte Carlo software
2002:Revolution Analytics
1699:Statistical software
255:, and parasitology.
1581:2015arXiv150603431K
1240:Nature Neuroscience
1146:10.1038/nature14140
1138:2015Natur.518...94G
1008:2017AtmEn.152..519W
617:2016ApJ...827L..38G
419:10.7717/peerj-cs.55
309:Metropolis–Hastings
161:Statistical package
32:
953:10.7717/peerj.2253
696:(6531): eabd9338.
228:tools. PyMC is an
145:Intel x86 – 32-bit
37:Original author(s)
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2190:
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1629:978-1-80512-716-1
1460:. 27 October 2020
1246:(11): 1462–1467.
282:Inference engines
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1982:Mathematica
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230:open source
203:written in
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1957:Statistics
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363:References
109:Written in
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53:2013-05-04
2173:for Excel
2117:SigmaStat
1992:OxMetrics
1934:Data Desk
1869:XLispStat
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