3 accepted papers
Computer simulations are amply utilized in scientific, industrial, and business environments for analyzing complex real-world phenomena. For a simulation to match realistic scenarios, it is often necessary to conduct time-consuming parameter calibration, i.e., finding the optimal simulation paramete…
We propose a novel calibration method for computer simulators, dealing with the problem of covariate shift.Covariate shift is the situation where input distributions for training and test are different, and ubiquitous in applications of simulations. Our approach is based on Bayesian inference with k…
We propose a novel approach to parameter estimation for simulator-based statistical models with intractable likelihood. Our proposed method involves recursive application of kernel ABC and kernel herding to the same observed data. We provide a theoretical explanation regarding why the approach works…