Infusion reference page

Infusion is an R package for Inference using
simulation,
available on CRAN.
The latest version (1.4.1, 2019-08-19) provides improved procedures for inference from simulation tables similar to those used in ABC. A gentle introduction with additional examples is available here.
In recent years, simulation methods such as approximate Bayesian computation (ABC) have extensively been used to infer parameters of population genetic models where the likelihood is intractable. Infusion implements an alternative approach, summary likelihood, that provides a likelihood-based analysis of the information retained in the summary statistics whose distribution is simulated. Rousset et al (2017) show that the method provides confidence intervals with controlled coverage independently of a prior distribution on parameters, in contrast to approximate Bayesian computation.
The latest version (1.4.1, 2019-08-19) provides improved procedures for inference from simulation tables similar to those used in ABC. A gentle introduction with additional examples is available here.
This page (C) F. Rousset 2016-present