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sparseVCBART
View on CRAN: Click
here
Download and install sparseVCBART package within the R console
Install from CRAN:
install.packages("sparseVCBART")
Install from Github:
library("remotes")
install_github("cran/sparseVCBART") Install by package version:
library("remotes")
install_version("sparseVCBART", "1.0.0") Attach the package and use:
library("sparseVCBART")
Maintained by
Sameer K. Deshpande
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[Scholar Profile | Author Map]
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First Published: 2026-05-19
Latest Update: 2026-05-19
Description:
Fits sparse linear varying coefficient models (VCMs), which assert a linear relationship between an outcome and several covariates that is allowed to change as functions of additional variables known as effect modifiers. Designed for high-dimensional settings where the number of covariates (i.e., number of slopes) is comparable to or larger than the number of observations. Approximates the coefficient functions using a version of Bayesian Additive Regression Trees that can perform global-local shrinkage. For more details see Ghosh, Bhogale, and Deshpande (2026+) <doi:10.48550/arXiv.2510.08204>.
How to cite:
Sameer K. Deshpande (2026). sparseVCBART: Sparse Varying Coefficient BART with Global-Local Priors". R package version 1.0.0, https://cran.r-project.org/web/packages/sparseVCBART. Accessed 05 Oct. 2026.
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