sparseVCBART
Sparse Varying Coefficient BART with Global-Local Priors"
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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.0 |
rolling linux/jammy R-4.5 | sparseVCBART_1.0.0.tar.gz |
254.2 KiB |
1.0.0 |
rolling linux/noble R-4.5 | sparseVCBART_1.0.0.tar.gz |
260.1 KiB |
1.0.0 |
rolling source/ R- | sparseVCBART_1.0.0.tar.gz |
54.0 KiB |
1.0.0 |
latest linux/jammy R-4.5 | sparseVCBART_1.0.0.tar.gz |
254.2 KiB |
1.0.0 |
latest linux/noble R-4.5 | sparseVCBART_1.0.0.tar.gz |
260.1 KiB |
1.0.0 |
latest source/ R- | sparseVCBART_1.0.0.tar.gz |
54.0 KiB |
1.0.0 |
2026-04-23 source/ R- | sparseVCBART_1.0.0.tar.gz |
0 B |