This project utilizes a series of non-informative priors to make sure the objectivity of the results. For example, this project sets the prior sample size to 1 to reduce the influence of the prior. This paper also uses a big prior variance to greatly support the parameter space while not conveying much information.
With the priors set then this paper uses Gibb’s sampling to simulate 5000 iterations and approximate the posterior distribution of the both levels.