- BART is a sum of trees model where each tree is constrained to be a weak learner.
- Initially, setup the model and define the prior distributions for the parameters of the trees. Initialize the trees and parameters as well.
- Use MCMC sampling to iteratively update the trees and parameters. At each iteration, update one tree while keeping the others fixed.
- After running the MCMC, use the samples to make predictions and quantify uncertainty.
- BART paper: https://rob-mcculloch.org/code/BART-7-05.pdf
- Boosted binary regression trees: https://www.mathworks.com/matlabcentral/fileexchange/42130-boosted-binary-regression-trees
- BART using MATLAB: https://github.com/weizhang-econ/BART_MATLAB/tree/main