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...

Celý popis

Podrobná bibliografie

Hlavní autoři:	Ritabrata Dutta, Marcel Schoengens, Lorenzo Pacchiardi, Avinash Ummadisingu, Nicole Widmer, Pierre Künzli, Jukka-Pekka Onnela, Antonietta Mira
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Foundation for Open Access Statistics 2021-11-01
Edice:	Journal of Statistical Software
Témata:	abc hpc spark mpi parallel imbalance python library
On-line přístup:	https://www.jstatsoft.org/index.php/jss/article/view/3554
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!