DTSR
0.2.2Distributed Trimmed Scores Regression for Handling Missing Data
Overview
Provides functions for handling missing data using Distributed Trimmed Scores Regression and other imputation methods. It includes facilities for data imputation, evaluation metrics, and clustering analysis. It is designed to work in distributed computing environments to handle large datasets efficiently. The philosophy of the package is described in Guo G. (2024) doi:10.1080/03610918.2022.2091779.
Install
Health
- OK2026-08-0513 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-06-216 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 0%
Downloads
Dependencies
Nothing depends on this yet.
Code & Tests
Datasets
People & History
3 releases. Pick two to compare their code metrics. R releases are shown for context.
- 0.2.2Latest
- unarchivedReturned to CRAN2026-06-20
- RR 4.6.0 released · 2026-04-24
- archivedRemoved from CRAN2025-07-10requires archived package 'DMwR2'
- 0.2.02025-04-27 · diff ↗
- RR 4.5.0 released · 2025-04-11
- 0.1.02024-11-08
- RR 4.4.0 released · 2024-04-24
Package metadata
- First published
- 2026-06-20
- Total releases
- 3 / 1 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 1.1 MB / 3 files
- Download size
- 1.2 MB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("DTSR")This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-08-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.