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bartBMA
View on CRAN: Click
here
Download and install bartBMA package within the R console
Install from CRAN:
install.packages("bartBMA")
Install from Github:
library("remotes")
install_github("cran/bartBMA")
Install by package version:
library("remotes")
install_version("bartBMA", "1.0")
Attach the package and use:
library("bartBMA")
Maintained by
Belinda Hernandez
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-03-13
Latest Update: 2020-03-13
Description:
"BART-BMA Bayesian Additive Regression Trees using Bayesian Model Averaging" (Hernandez B, Raftery A.E., Parnell A.C. (2018) ) is an extension to the original BART sum-of-trees model (Chipman et al 2010). BART-BMA differs to the original BART model in two main aspects in order to implement a greedy model which
will be computationally feasible for high dimensional data. Firstly BART-BMA uses a greedy search for the best split points and variables when growing decision trees within each sum-of-trees
model. This means trees are only grown based on the most predictive set of split rules. Also rather than using Markov chain Monte Carlo (MCMC), BART-BMA uses a greedy implementation of Bayesian Model Averaging called Occam's Window
which take a weighted average over multiple sum-of-trees models to form its overall prediction. This means that only the set of sum-of-trees for which there is high support from the data
are saved to memory and used in the final model.
How to cite:
Belinda Hernandez (2020). bartBMA: Bayesian Additive Regression Trees using Bayesian Model
Averaging. R package version 1.0, https://cran.r-project.org/web/packages/bartBMA
Previous versions and publish date:
1.0 (2020-03-13 12:50)
Other packages that cited bartBMA R package
View bartBMA citation profile
Other R packages that bartBMA depends,
imports, suggests or enhances
Functions, R codes and Examples using
the bartBMA R package
Some associated functions: ITEs_CATT_bartBMA_exact_par . ITEs_bartBMA . ITEs_bartBMA_exact_par . bartBMA . bartBMA_with_ITEs_exact_par . pred_expectation_intervals_bbma_GS . pred_intervals_bbma_GS . pred_intervals_new_initials_GS . pred_ints_exact . pred_ints_exact_par . pred_means_bbma_GS . pred_means_bbma_new_initials_GS . predict_bartBMA . predict_probit_bartBMA . preds_bbma_lin_alg . probit_bartBMA . varImpScores . varIncProb .
Some associated R codes: ITEs_CATT_bartBMA_exact_par.R . ITEs_bartBMA.R . ITEs_bartBMA_exact_par.R . RcppExports.R . bartBMA.R . bartBMA_with_ITEs_exact_par.R . pred_expectation_intervals_bbma_GS.R . pred_intervals_GS.R . pred_intervals_new_initials_GS.R . pred_ints_exact.R . pred_ints_exact_par.R . pred_means_bbma_GS.R . pred_means_new_initials_GS.R . predict_bartBMA.R . predict_probit_bartBMA.R . preds_bbma_lin_alg.R . printbartBMA.R . probit_bartBMA.R . varImpScores.R . varIncProb.R . Full bartBMA package functions and examples
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