STAN is the leading Bayesian engine for R, both for academia and the industry. Its performance is very good, mainly because it is written in C++.
In Bayesian statistics, and we have a very different approach than in classical statistics. Here, each coefficient will behave as a random variable, and we will use appropriate algorithms to recover the distribution of each one of them. But there is an extra element here, we will be able to incorporate prior distributions into our approach. Consequently, the idea will be the following:
Bayesian statistics could be interpreted as an approach where we have a prior/initial idea about a coefficient, we then augment that expectation using the data, and we finally end up with a posterior distribution. This is not that different from the process humans follow when learning new things; for example, we...
