[D] When are MCMC methods used for the BART model?

I am studying the BART (Bayesian Additive Regression Trees) model from the following articles: Chipman 2010, Chipman 2007 and Chipman 1998. At the moment I understand this from the model for classification:

Prior distribution in trees P(T):

P(split) =α(1+d)^-β

Prior distribution in terminal nodes P(µ):

µ ~ N (0,σ_{µ}^2)

Prior distribution for P(σ):

Inverse Chi (it's = 1 for classification problems)

I know that MCMC looks for values for parameters. In the article they recommend values for …

machinelearning mcmc