BART-package: Bayesian Additive Regression Trees
In BART: Bayesian Additive Regression Trees
BART-package R Documentation
Bayesian Additive Regression Trees
Description
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>.
References
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>.
Chipman H., George E. and McCulloch R. (1998)
Bayesian CART Model Search.
JASA, 93, 935-948.
<doi:10.1080/01621459.1998.10473750>.
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>.
Gramacy R. and Polson N. (2012)
Simulation-based regularized logistic regression.
Bayesian Analysis, 7, 567-590.
<doi:10.1214/12-ba719>.
Albert J. and Chib S. (1993)
Bayesian Analysis of Binary and Polychotomous Response Data.
JASA, 88, 669-679.
<doi:10.1080/01621459.1993.10476321>.
De Waal T., Pannekoek J. and Scholtus S. (2011)
Handbook of statistical data editing and imputation.
John Wiley & Sons, Hoboken, NJ.
Friedman J. (1991)
Multivariate adaptive regression splines.
Annals of Statistics, 19, 1-67.
Friedman J. (2001)
Greedy Function Approximation: A Gradient Boosting Machine.
Annals of Statistics, 29, 1189-1232.
Holmes C. and Held L. (2006)
Bayesian auxiliary variable models for binary and multinomial regression.
Bayesian Analysis, 1, 145-168.
<doi:10.1214/06-ba105>.
Linero A. (2018)
Bayesian regression trees for high dimensional prediction and variable selection.
JASA, 113, 626-636.
<doi:10.1080/01621459.2016.1264957>.
BART documentation built on June 22, 2024, 11:33 a.m.
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| BART-package | R Documentation |
Bayesian Additive Regression Trees
Description
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>.
References
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>.
Chipman H., George E. and McCulloch R. (1998) Bayesian CART Model Search. JASA, 93, 935-948. <doi:10.1080/01621459.1998.10473750>.
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>.
Gramacy R. and Polson N. (2012) Simulation-based regularized logistic regression. Bayesian Analysis, 7, 567-590. <doi:10.1214/12-ba719>.
Albert J. and Chib S. (1993) Bayesian Analysis of Binary and Polychotomous Response Data. JASA, 88, 669-679. <doi:10.1080/01621459.1993.10476321>.
De Waal T., Pannekoek J. and Scholtus S. (2011) Handbook of statistical data editing and imputation. John Wiley & Sons, Hoboken, NJ.
Friedman J. (1991) Multivariate adaptive regression splines. Annals of Statistics, 19, 1-67.
Friedman J. (2001) Greedy Function Approximation: A Gradient Boosting Machine. Annals of Statistics, 29, 1189-1232.
Holmes C. and Held L. (2006) Bayesian auxiliary variable models for binary and multinomial regression. Bayesian Analysis, 1, 145-168. <doi:10.1214/06-ba105>.
Linero A. (2018) Bayesian regression trees for high dimensional prediction and variable selection. JASA, 113, 626-636. <doi:10.1080/01621459.2016.1264957>.
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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