Approximate Bayesian computation: Difference between revisions

Revision as of 11:02, 4 May 2021

Revision as of 10:46, 5 May 2021

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| [https://abcpy.readthedocs.io/en/latest/ ABCpy]

| Python package for ABC and other likelihood-free inference schemes. Several state-of-the-art algorithms available. Provides quick way to integrate existing generative (from C++, R etc.), user-friendly parallelization using MPI or Spark and summary statistics learning (with neural network or linear regression).

| <ref>{{cite journalarXiv |title=ABCpy: A High-Performance Computing Perspective to Approximate Bayesian Computation. |last1=Dutta |first1=R |last2=Schoengens |first2=M |last3=Pacchiardi |first3=L |last4=Ummadisingu |first4=A |last5=Widmer |first5=N |last6=Onnela |first6=J. P. |last7=Mira |first7=A

|year=2020|arxiv=1711.04694 }}</ref>

|}