sparseVCBART
1.0.0Sparse Varying Coefficient BART with Global-Local Priors"
Overview
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.
Install
Health
- OK2026-08-0413 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-05-207 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 84%
- Return-value docs
- 100%
- References docs
- 25%
Downloads
Repository
Repository practices
1 development-tooling and community-health practice detected across 1 family in the upstream repository
Checks run against github.com/ghoshstats/sparsevcbart on 2026-08-23.
Dependencies
Nothing depends on this yet.
Code & Tests
People & History
1 release. R releases are shown for context.
- 1.0.0Latest2026-05-19 · current release
- RR 4.6.0 released · 2026-04-24
Package metadata
- First published
- 2026-05-19
- Total releases
- 1 / 1 yrs
- License
- GPL (>= 3) OSI
- Download size
- 54 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
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