**R**itabrata Dutta, Marcel Schöengens, Jukka-Pekka Onnela, and Antonietta Mira recently put a new ABC software on-line, called ABCpy for ABC with Python. The software aims at an automated parallelisation of ABC runs, requiring only code to generate from the (generative) model and the choice of summary statistics and of associated distance. Alternatively an approximate likelihood (as in synthetic likelihood) can be used. The tolerance ε is chosen as a percentile of the prior predictive distribution on the distance. The versions of ABC found in ABCpy are

- Population Monte Carlo for ABC (PMCABC);
- sequential Monte Carlo ABC (ABC-SMC);
- replenishment Sequential Monte Carlo ABC (RSMC-ABC);
- adaptive Population Monte Carlo ABC (APMCABC);
- ABC with subset simulation (ABCsubsim); and
- simulated annealing ABC (SABC)

Anto mentioned ABCpy to me while in Harvard last week and I have not tested the program (my only brush with Python being the occasional call to latex2wp for SeriesB’log). And obviously, writing a blog about Monte (Carlo and) Python makes a link to the Monty Pythons irresistible: