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ABCpy: A High-Performance Computing Perspective to Approximate Bayesian Computation

ABCpy is a highly modular scientific library for approximate Bayesian computation (ABC) written in Python. The main contribution of this paper is to document a software engineering effort that enables domain scientists to easily apply ABC to their research without being ABC experts; using ABCpy they...

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Tallennettuna:
Päätekijät: Ritabrata Dutta, Marcel Schoengens, Lorenzo Pacchiardi, Avinash Ummadisingu, Nicole Widmer, Pierre Künzli, Jukka-Pekka Onnela, Antonietta Mira
Aineistotyyppi: Artigo
Kieli:Inglês
Julkaistu: Foundation for Open Access Statistics 2021-11-01
Sarja:Journal of Statistical Software
Aiheet:
abc
hpc
spark
mpi
parallel
imbalance
python library
Linkit:https://www.jstatsoft.org/index.php/jss/article/view/3554
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