Corpus ID: 88513132

Bayesian Additive Regression Trees With Parametric Models of Heteroskedasticity

@inproceedings{Bleich2014BayesianAR,
  title={Bayesian Additive Regression Trees With Parametric Models of Heteroskedasticity},
  author={Justin Bleich and Adam Kapelner},
  year={2014}
}
  • Justin Bleich, Adam Kapelner
  • Published 2014
  • Mathematics
  • We incorporate heteroskedasticity into Bayesian Additive Regression Trees (BART) by modeling the log of the error variance parameter as a linear function of prespecified covariates. Under this scheme, the Gibbs sampling procedure for the original sum-of- trees model is easily modified, and the parameters for the variance model are updated via a Metropolis-Hastings step. We demonstrate the promise of our approach by providing more appropriate posterior predictive intervals than homoskedastic… CONTINUE READING

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