BIDC: Bayesian Inference for Default Correlations
I just released a package on Github called BIDC, which stands for Bayesian Inference for Default Correlations. I started working on this together with my colleague Victor Medina back when I was a financial stability analyst at the Superintendency of Banks and Financial Institutions in Chile. In fact, you can see the slides from our presentation at the 2017 version of SBIF conference here (Biron and Medina 2017). The difference is that, instead of Stan, the method available in BIDC uses a Metropolis-Hastings-within-Gibbs MCMC sampler (Gilks 1996) written entirely in base R, that runs much faster. Currently, it only supports the naive version shown on those slides.