Package: iBART 1.0.2

iBART: Iterative Bayesian Additive Regression Trees Descriptor Selection Method

A statistical method based on Bayesian Additive Regression Trees with Global Standard Error Permutation Test (BART-G.SE) for descriptor selection and symbolic regression. It finds the symbolic formula of the regression function y=f(x) as described in Ye, Senftle, and Li (2023) <https://www.tandfonline.com/doi/abs/10.1080/01621459.2023.2294527>.

Authors:Shengbin Ye [aut, cre, cph], Meng Li [aut]

iBART_1.0.2.tar.gz
iBART_1.0.2.zip(r-4.5)iBART_1.0.2.zip(r-4.4)iBART_1.0.2.zip(r-4.3)
iBART_1.0.2.tgz(r-4.4-any)iBART_1.0.2.tgz(r-4.3-any)
iBART_1.0.2.tar.gz(r-4.5-noble)iBART_1.0.2.tar.gz(r-4.4-noble)
iBART_1.0.2.tgz(r-4.4-emscripten)iBART_1.0.2.tgz(r-4.3-emscripten)
iBART.pdf |iBART.html✨
iBART/json (API)
NEWS

# Install 'iBART' in R:
install.packages('iBART', repos = c('https://mattsheng.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/mattsheng/ibart/issues

Uses libs:
  • openjdk– OpenJDK Java runtime, using Hotspot JIT
Datasets:

On CRAN:

3 exports 7 stars 1.59 score 19 dependencies 16 scripts 210 downloads

Last updated 3 months agofrom:00eefa7419. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 13 2024
R-4.5-winOKSep 13 2024
R-4.5-linuxOKSep 13 2024
R-4.4-winOKSep 13 2024
R-4.4-macOKSep 13 2024
R-4.3-winOKSep 13 2024
R-4.3-macOKSep 13 2024

Exports:generate_unitiBARTk_var_model

Dependencies:bartMachinebartMachineJARscodetoolsdigestdoRNGforeachglmnetiteratorsitertoolslatticeMatrixmissForestrandomForestRcppRcppEigenrJavarngtoolsshapesurvival

Complex Model Simulation

Rendered fromsimulation.Rmdusingknitr::rmarkdownon Sep 13 2024.

Last update: 2024-06-15
Started: 2023-11-11

Single-Atom Catalysis Data Analysis

Rendered fromreal_data.Rmdusingknitr::rmarkdownon Sep 13 2024.

Last update: 2024-06-15
Started: 2023-11-11