Supplement to “A Comparative Review of Dimension Reduction Methods in Approximate
Bayesian Computation”. The supplement contains for each of the three examples a …

Abstract Approximate Bayesian Computation (ABC) methods, also known as likelihood-free
techniques, have appeared in the past ten years as the most satisfactory approach to …

Many modern statistical applications involve inference for complex stochastic models, where
it is easy to simulate from the models, but impossible to calculate likelihoods. Approximate …

Approximate Bayesian computation (ABC) has gained popularity over the past few years for
the analysis of complex models arising in population genetics, epidemiology and system …

OBJECTIVE There is limited information on the normal appearance of the cisterna chyli (CC)
in cats on CT and MRI. The aim of this retrospective study was to describe the CT and MRI …

This chapter explains an intuitive exploration of the basics of approximate Bayesian
computation (ABC) methods, and illustrates wherever possible by simple examples. It …

This chapter surveys the various forms of approximate Bayesian computation (ABC)
algorithms that have been developed to sample from pABC. The earliest ABC samplers …

Approximate Bayesian computation (ABC) is a popular technique for analysing data for
complex models where the likelihood function is intractable. It involves using simulation from …

Many models of interest in the natural and social sciences have no closed-form likelihood
function, which means that they cannot be treated using the usual techniques of statistical …

The 21st century has seen an enormous growth in the development and use of approximate
Bayesian methods. Such methods produce computational solutions to certain “intractable” …