NEWS for SBMTrees

Version 1.2 (2024-12-10) - Bug Fix Release

Changes: - Clang-asan Fixes: Addressed and fixed bugs identified by Clang AddressSanitizer (ASan) checks, improving memory safety and stability.

No new features have been added in this release. The focus was on ensuring robustness and reliability by resolving memory-related issues flagged during the ASan testing process.

Version 1.1 (2024-12-04) - Initial Release

This release introduces the SBMTrees package, which implements a Bayesian non-parametric framework for imputing missing covariates and outcomes in longitudinal data under the Missing at Random (MAR) assumption. The core model, Bayesian Trees Mixed-Effects Model (BMTrees), extends Mixed-Effects BART by using centralized Dirichlet Process (CDP) Normal Mixture priors, allowing it to handle non-normal random effects and errors, address model misspecification, and capture complex relationships in longitudinal data.

Features:

• BMTrees Prediction: Predicts longitudinal outcomes based on mixed-effects models.
• Sequential Imputation: Imputes missing covariates and outcomes in longitudinal datasets with flexibility in specifying priors for random effects and errors.
• Efficient Gibbs sampling: Implemented in C++ for improved performance.
• Integration with mixedBART: Includes mixedBART as a baseline model for additional flexibility in handling data.

Key Functionalities:

• BMTrees_prediction: Predicts longitudinal outcomes based on mixed-effects models.
• sequential_imputation: Handles missing data imputation sequentially in longitudinal datasets.

License:

This package is licensed under the GNU General Public License version 2 (GPL-2). The core computations leverage code derived from the BART3 package, originally developed by Rodney Sparapani, which is also under GPL-2.

Known Issues:

• No significant issues at the moment. For more details on potential limitations, please refer to the documentation.