sbim - Simulation-Based Inference using a Metamodel for Log-Likelihood
Estimator
Parameter inference methods for models defined implicitly
using a random simulator. Inference is carried out using
simulation-based estimates of the log-likelihood of the data.
The inference methods implemented in this package are explained
in Park, J. (2025) <doi:10.48550/arxiv.2311.09446>. These
methods are built on a simulation metamodel which assumes that
the estimates of the log-likelihood are approximately normally
distributed with the mean function that is locally quadratic
around its maximum. Parameter estimation and uncertainty
quantification can be carried out using the ht() function (for
hypothesis testing) and the ci() function (for constructing a
confidence interval for one-dimensional parameters).