srlars
3.0.1Fast and Scalable Cellwise-Robust Ensemble
Overview
Functions to perform robust variable selection and regression using the Fast and Scalable Cellwise-Robust Ensemble (FSCRE) algorithm. The approach establishes a robust foundation using the Detect Deviating Cells (DDC) algorithm and robust correlation estimates. It then employs a competitive ensemble architecture where a robust Least Angle Regression (LARS) engine proposes candidate variables and cross-validation arbitrates their assignment. A final robust MM-estimator is applied to the selected predictors.
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
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 0%
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Dependencies
Code & Tests
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6 releases. Pick two to compare their code metrics. R releases are shown for context.
Package metadata
- First published
- 2023-06-29
- Total releases
- 6 / 3 yrs
- License
- GPL (>= 2) OSI
- Download size
- 18 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
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