The LIC Criterion for Optimal Subset Selection
Overview
The LIC criterion is to determine the most informative subsets so that the subset can retain most of the information contained in the complete data. The philosophy of the package is described in Guo G. (2022) doi:10.1080/02664763.2022.2053949.
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 8
- Examples that run
- 100%8 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 38%
Downloads
Dependencies
Installing LIC adds no packages beyond those that come with R.
Code & Tests
Datasets
People & History
Pick two releases to compare their code metrics.
- 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
- RR 4.2.0 released · 2022-04-22
- 0.0.2Latest
- 0.0.12021-10-08
- RR 4.1.0 released · 2021-05-18
Package metadata
- First published
- 2021-10-08
- Total releases
- 2 / 5 yrs
- License
- MIT + file LICENSE OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 234 KB / 3 files
- Download size
- 237 KB
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("LIC")This package has no citation file, so citation() returns this entry built from DESCRIPTION.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-24, which the citation names so these numbers can be found later. More on citing and the projects behind them.