IOLS
0.1.4Iterated Ordinary Least Squares Regression
Overview
Addresses the 'log of zero' by developing a new family of estimators called iterated Ordinary Least Squares. This family nests standard approaches such as log-linear and Poisson regressions, offers several computational advantages, and corresponds to the correct way to perform the popular log(Y + 1) transformation. For more details about how to use it, see the notebook at: https://www.davidbenatia.com/.
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
- OK2026-06-0913 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-06-0812 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-03-1314 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Show 2 earlier snapshots
- WARNING2026-03-1213 OK · 0 NOTE · 1 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%
Downloads
Dependencies
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Code & Tests
Datasets
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Package metadata
- First published
- 2022-11-08
- Total releases
- 5 / 4 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 2.10
- Bundled data
- 19 KB / 1 file
- Download size
- 28 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("IOLS")This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.
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