To avoid duplication, the main references that this package relies upon appear here only. For more information see Sparapani, Spanbauer and McCulloch <doi:10.18637/jss.v097.i01>.
Sparapani R., Spanbauer C. and McCulloch R. (2021) Nonparametric Machine Learning and Efficient Computation with Bayesian Additive Regression Trees: The BART R Package. JSS, 97, 1-66. <doi:10.18637/jss.v097.i01>.
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Chipman H., George E., and McCulloch R. (2010) Bayesian Additive Regression Trees. Annals of Applied Statistics, 4, 266-298. <doi:10.1214/09-AOAS285>.
Sparapani R., Logan B., McCulloch R. and Laud P. (2016) Nonparametric Survival Analysis Using Bayesian Additive Regression Trees (BART). Statistics in Medicine, 35, 2741-2753. <doi:10.1002/sim.6893>.
Sparapani R., Logan B., McCulloch R. and Laud P. (2020) Nonparametric Competing Risks Analysis Using Bayesian Additive Regression Trees (BART). SMMR, 29, 57-77. <doi:10.1177/0962280218822140>.
Sparapani R., Rein L., Tarima S., Jackson T. and Meurer J. (2020) Non-Parametric Recurrent Events Analysis with BART and an Application to the Hospital Admissions of Patients with Diabetes. Biostatistics, 21, 69-85. <doi:10.1093/biostatistics/kxy032>.
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