CRAN/E | robust2sls

robust2sls

Outlier Robust Two-Stage Least Squares Inference and Testing

Installation

About

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) .

github.com/jkurle/robust2sls
Bug report File report

Key Metrics

Version 0.2.2
R ≥ 2.10
Published 2023-01-11 442 days ago
Needs compilation? no
License GPL-3
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Maintainer

Maintainer

Jonas Kurle

mail@jonaskurle.com

Authors

Jonas Kurle

aut / cre

Material

README
NEWS
Reference manual
Package source

Vignettes

Monte Carlo Simulations
Outlier Testing
Introduction to the robust2sls Package

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

robust2sls archive

Depends

R ≥ 2.10

Imports

exactci
foreach
ivreg
MASS
mathjaxr
pracma
stats

Suggests

covr
datasets
doFuture
doParallel
doRNG
future
ggplot2
grDevices
ivgets
knitr
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utils