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robust2sls  

Outlier Robust Two-Stage Least Squares Inference and Testing
View on CRAN: Click here


Download and install robust2sls package within the R console
Install from CRAN:
install.packages("robust2sls")

Install from Github:
library("remotes")
install_github("cran/robust2sls")

Install by package version:
library("remotes")
install_version("robust2sls", "0.2.2")



Attach the package and use:
library("robust2sls")
Maintained by
Jonas Kurle
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-11-23
Latest Update: 2023-01-11
Description:
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) .
How to cite:
Jonas Kurle (2021). robust2sls: Outlier Robust Two-Stage Least Squares Inference and Testing. R package version 0.2.2, https://cran.r-project.org/web/packages/robust2sls. Accessed 21 Nov. 2024.
Previous versions and publish date:
0.1.0 (2021-11-23 08:50), 0.2.0 (2022-02-14 13:30), 0.2.1 (2022-08-15 13:30)
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