robust2sls
0.2.3Outlier Robust Two-Stage Least Squares Inference and Testing
Overview
An implementation of easy tools for outlier robust inference in two-stage least squares (2SLS) models. The user specifies a reference distribution against which observations are classified as outliers or not. After removing the outliers, adjusted standard errors are automatically provided. Furthermore, several statistical tests for the false outlier detection rate can be calculated. The outlier removing algorithm can be iterated a fixed number of times or until the procedure converges. The algorithms and robust inference are described in more detail in Jiao (2019) https://drive.google.com/file/d/1qPxDJnLlzLqdk94X9wwVASptf1MPpI2w/view.
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- OK2026-08-0413 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
- WARNING2026-06-0712 OK · 0 NOTE · 1 WARNING · 0 ERROR · 0 FAILURE
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- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
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- References docs
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Package metadata
- First published
- 2021-11-23
- Total releases
- 5 / 5 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 2.10
- Download size
- 372 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
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