Sparse Varying Coefficient BART with Global-Local Priors" R package sparseVCBART version 1.0.0 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>. Software Imports: Rcpp, MASS LinkingTo: Rcpp, RcppArmadillo Sameer K. Deshpande <sameer.deshpande@wisc.edu> Comprehensive R Archive Network (CRAN) Soham Ghosh [aut], Sameer K. Deshpande [cre, aut] (ORCID: <https://orcid.org/0000-0003-4116-5533>) GPL (>= 3) 2026-05-19 application/tgz https://CRAN.R-project.org/package=sparseVCBART doi:10.32614/CRAN.package.sparseVCBART