The Inverse Uncertainty Quantification study type is used to compute the posterior distribution of all calibration parameters based on the experimental data and the prior distribution of the calibration parameters. The MCMC method is used to construct Markov chains where the sampled data from a converged Markov chain is based on the posterior distribution. More details of Inverse Uncertainty Quantification can be found in Inverse Uncertainty Quantification — Markov Chain Monte Carlo.