stepgbm
1.0.1Stepwise Variable Selection for Generalized Boosted Regression Modeling
Overview
An introduction to a couple of novel predictive variable selection methods for generalised boosted regression modeling (gbm). They are based on various variable influence methods (i.e., relative variable influence (RVI) and knowledge informed RVI (i.e., KIRVI, and KIRVI2)) that adopted similar ideas as AVI, KIAVI and KIAVI2 in the 'steprf' package, and also based on predictive accuracy in stepwise algorithms. For details of the variable selection methods, please see: Li, J., Siwabessy, J., Huang, Z. and Nichol, S. (2019) doi:10.3390/geosciences9040180. Li, J., Alvarez, B., Siwabessy, J., Tran, M., Huang, Z., Przeslawski, R., Radke, L., Howard, F., Nichol, S. (2017). <DOI: 10.13140/RG.2.2.27686.22085>.
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
- OK2026-06-0913 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-06-0812 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 0%
- Documented parameters
- 91%
- Return-value docs
- 100%
- References docs
- 67%
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Code & Tests
People & History
2 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- 1.0.1Latest
- RR 4.2.0 released · 2022-04-22
- 1.0.02021-12-10
- RR 4.1.0 released · 2021-05-18
Package metadata
- First published
- 2021-12-10
- Total releases
- 2 / 5 yrs
- License
- GPL (>= 2) OSI
- Minimum R
- ≥ 4.0
- Download size
- 7.9 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
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