LinRegOutliers
LinRegOutliers: A Julia package for detecting outliers in linear regression - Published in JOSS (2021)
Science Score: 95.0%
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Published in Journal of Open Source Software
Keywords
Repository
Direct and robust methods for outlier detection in linear regression
Basic Info
Statistics
- Stars: 48
- Watchers: 3
- Forks: 6
- Open Issues: 1
- Releases: 63
Topics
Metadata Files
README.md
LinRegOutliers
A Julia package for outlier detection in linear regression.
Implemented Methods
- Ordinary Least Squares and Weighted Least Squares regression
- Regression diagnostics (DFBETA, DFFIT, CovRatio, Cook's Distance, Mahalanobis, Hadi's measure, etc.)
- Hadi & Simonoff (1993)
- Kianifard & Swallow (1989)
- Sebert & Montgomery & Rollier (1998)
- Least Median of Squares
- Least Trimmed Squares
- Minimum Volume Ellipsoid (MVE)
- MVE & LTS Plot
- Billor & Chatterjee & Hadi (2006)
- Pena & Yohai (1995)
- Satman (2013)
- Satman (2015)
- Setan & Halim & Mohd (2000)
- Least Absolute Deviations (LAD)
- Quantile Regression Parameter Estimation (quantileregression)
- Least Trimmed Absolute Deviations (LTA)
- Hadi (1992)
- Marchette & Solka (2003) Data Images
- Satman's GA based LTS estimation (2012)
- Fischler & Bolles (1981) RANSAC Algorithm
- Minimum Covariance Determinant Estimator
- Imon (2005) Algorithm
- Barratt & Angeris & Boyd (2020) CCF algorithm
- Atkinson (1994) Forward Search Algorithm
- BACON Algorithm (Billor & Hadi & Velleman (2000))
- Hadi (1994) Algorithm
- Chatterjee & Mächler (1997)
- Theil-Sen estimator for multiple regression
- Deepest Regression Estimator
- Robust Hat Matrix based Initial Subset Regressor
- Summary
Unimplemented Methods
- Pena & Yohai (1999). See #25 for the related issue.
Installation
LinRegOutliers can be installed using the Julia REPL.
julia
julia> ]
(@v1.11) pkg> add LinRegOutliers
or
julia
julia> using Pgk
julia> Pkg.add("LinRegOutliers")
then
julia
julia> using LinRegOutliers
to make all the stuff be ready!
Examples
We provide some examples here.
Documentation
Please check out the reference manual here.
News
- We implemented ~25 outlier detection algorithms which covers a high percentage of the literature.
- Visit the CHANGELOG.md for the log of latest changes.
Contributions
You are probably the right contributor
- If you have statistics background
- If you like Julia
However, the second condition is more important because an outlier detection algorithm is just an algorithm. Reading the implemented methods is enough to implement new ones. Please follow the issues. Here is the a bunch of first shot introductions for new comers. Welcome and thank you in advance!
Citation
Please refer our original paper if you use the package in your research using
Satman et al., (2021). LinRegOutliers: A Julia package for detecting outliers in linear regression. Journal of Open Source Software, 6(57), 2892, https://doi.org/10.21105/joss.02892
or the bibtex entry
bibtex
@article{Satman2021,
doi = {10.21105/joss.02892},
url = {https://doi.org/10.21105/joss.02892},
year = {2021},
publisher = {The Open Journal},
volume = {6},
number = {57},
pages = {2892},
author = {Mehmet Hakan Satman and Shreesh Adiga and Guillermo Angeris and Emre Akadal},
title = {LinRegOutliers: A Julia package for detecting outliers in linear regression},
journal = {Journal of Open Source Software}
}
Contact & Communication
- Please use issues for a new feature request or bug reports.
- We are in #linregoutliers channel on Julia Slack for any discussion requires online chatting.
Owner
- Name: Mehmet Hakan Satman
- Login: jbytecode
- Kind: user
- Location: Istanbul
- Company: Istanbul University
- Twitter: mhsatman
- Repositories: 14
- Profile: https://github.com/jbytecode
Professor of Numerical Methods
JOSS Publication
LinRegOutliers: A Julia package for detecting outliers in linear regression
Authors
Department of Econometrics, Istanbul University, Istanbul, Turkey
Department of Electronics and Communication Engineering, RV College of Engineering, Bengaluru, India
Department of Electrical Engineering, Stanford University, Stanford, California, USA
Department of Informatics, Istanbul University, Istanbul, Turkey
Editor
Mikkel Meyer Andersen
Tags
linear regression outlier detection robust statisticsGitHub Events
Total
- Create event: 1
- Commit comment event: 2
- Release event: 1
- Watch event: 3
- Issue comment event: 8
- Push event: 25
Last Year
- Create event: 1
- Commit comment event: 2
- Release event: 1
- Watch event: 3
- Issue comment event: 8
- Push event: 25
Committers
Last synced: 5 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| jbytecode | m****n@g****m | 479 |
| guille | a****s@s****u | 15 |
| Shreesh Adiga | 1****h@g****m | 11 |
| Emre Akadal | e****l@g****m | 3 |
| Tim Holy | t****y@g****m | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 4 months ago
All Time
- Total issues: 25
- Total pull requests: 19
- Average time to close issues: 5 months
- Average time to close pull requests: about 1 hour
- Total issue authors: 6
- Total pull request authors: 5
- Average comments per issue: 6.8
- Average comments per pull request: 0.89
- Merged pull requests: 19
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- jbytecode (18)
- salleuska (3)
- stevenaleung (1)
- PaulSoderlind (1)
- angeris (1)
- JuliaTagBot (1)
Pull Request Authors
- tantei3 (9)
- angeris (5)
- jbytecode (2)
- akadal (2)
- timholy (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
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Total downloads:
- julia 10 total
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 62
juliahub.com: LinRegOutliers
Direct and robust methods for outlier detection in linear regression
- Documentation: https://docs.juliahub.com/General/LinRegOutliers/stable/
- License: MIT
-
Latest release: 0.11.6
published 7 months ago
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