Linear Regression Based on 'ILSE' for Missing Data
Overview
Linear regression when covariates include missing values by embedding the correlation information between covariates. Especially for block missing data, it works well. 'ILSE' conducts imputation and regression simultaneously and iteratively. More details can be referred to Huazhen Lin, Wei Liu and Wei Lan. (2021) doi:10.1080/07350015.2019.1635486.
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Documentation
- Help pages
- 9
- Examples that run
- 100%9 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 33%
Downloads
Dependencies
Code & Tests
Datasets
People & History
Pick two releases to compare their code metrics.
- RR 4.6.0 released · 2026-04-24
- archivedRemoved from CRAN2025-09-17email to the maintainer is undeliverable
- 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
- 1.1.7
- 1.1.62022-01-07
- RR 4.1.0 released · 2021-05-18
Package metadata
- First published
- 2022-01-07
- Total releases
- 2 / 4 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 3.0.1
- Bundled data
- 0.4 KB / 1 file
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citation("ILSE")This package has no citation file, so citation() returns this entry built from DESCRIPTION.
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