Package: robust2sls 0.2.4

Jonas Kurle

robust2sls: Outlier Robust Two-Stage Least Squares Inference and Testing

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>.

Authors:Jonas Kurle [aut, cre]

robust2sls_0.2.4.tar.gz
robust2sls_0.2.4.zip(r-4.7-any)robust2sls_0.2.4.zip(r-4.6-any)robust2sls_0.2.4.zip(r-4.5-any)
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robust2sls_0.2.4.tar.gz(r-4.7-any)robust2sls_0.2.4.tar.gz(r-4.6-any)
robust2sls_0.2.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
robust2sls/json (API)

# Install 'robust2sls' in R:
install.packages('robust2sls', repos = c('https://jkurle.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/jkurle/robust2sls/issues

On CRAN:

Conda:

4.56 score 1 stars 24 scripts 339 downloads 39 exports 93 dependencies

Last updated from:ae471066d0. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK134
source / vignettesOK259
linux-releaseOK160
macos-releaseOK121
macos-oldrelOK97
windows-develOK88
windows-releaseOK89
windows-oldrelOK58
wasm-releaseOK119

Exports:beta_hausmanbeta_infbeta_inf_correctionbeta_tbeta_test_avarcase_resamplingcount_indicescounttestestimate_paramestimate_param_nullevaluate_bootextract_bootextract_formulagauge_avargauge_covargenerate_datagenerate_paramglobaltestiis_initmc_gridmulti_cutoffmvn_supnonmissingnonparametricnonparametric_resamplingoutlieroutlier_detectionoutliersoutliers_propproptestrobustified_initsaturated_initselection_iissimessumtestsuptestuser_initvalidate_robust2slsvarrho

Dependencies:abindbackportsbootbriobroomcallrcarcarDataclicodetoolscolorspacecowplotcpp11crayonDerivdescdiffobjdoBydplyrevaluateexactcifarverforeachforecastFormulafracdifffsgenericsggplot2gluegtableisobanditeratorsivregjsonlitelabelinglatticelifecyclelme4lmtestmagrittrMASSmathjaxrMatrixMatrixModelsmgcvminqamodelrnlmenloptrnnetnumDerivotelpbkrtestpillarpkgbuildpkgconfigpkgloadpracmapraiseprocessxpspurrrquantregR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrlangrprojrootS7scalesSparseMssanvstringistringrsurvivaltestthattibbletidyrtidyselecttimeDateurcautf8vctrsviridisLitewaldowithrzoo

Introduction to the robust2sls Package
Overview | Model setup | Outlier detection algorithms | Initial estimator | Reference distribution | Cut-off or probability of outliers | Iteration | Example without outliers | Data generating process (DGP) | Outlier detection | Robustified 2SLS | Saturated 2SLS | Inference under Null hypothesis of no outliers | Testing for difference in coefficient estimates | Example with outliers | Data
Rendered fromoverview.Rmdusingknitr::rmarkdown

Last update: 2026-08-14
Started: 2021-11-14

Monte Carlo Simulations
Introduction | Step 1: True model | Step 2: Outlier detection algorithm | Step 3: Parameter settings | Step 4: Backend for execution | Parallel loop | Sequential loop
Rendered frommonte-carlo.Rmdusingknitr::rmarkdown

Last update: 2026-08-14
Started: 2021-05-01

Outlier Testing
Introduction | Artificial Data | Outlier Detection | Proportion Test | Count Test | Scaling Sum Test | Scaling Supremum Test
Rendered fromoutlier-testing.Rmdusingknitr::rmarkdown

Last update: 2026-08-14
Started: 2022-02-14

Readme and manuals

Help Manual

Help pageTopics
robust2sls: A package for outlier robust 2SLS inference and testingrobust2sls-package robust2sls
Calculates a Hausman test on the difference between robust and full sample estimatesbeta_hausman
Calculates valid se for coefficients under H0 of no outliersbeta_inf
Calculates the correction factor for inference under H0 of no outliersbeta_inf_correction
Conducts a t-test on the difference between robust and full sample estimatesbeta_t
Calculates the asymptotic variance of the difference between robust and full sample estimators of the structural parametersbeta_test_avar
Uses nonparametric case resampling for standard errors of parameters and gaugecase_resampling
Counts the number of times each index was sampledcount_indices
Count testcounttest
Estimation of moments of the dataestimate_param
Estimation of moments of the dataestimate_param_null
Evaluate bootstrap resultsevaluate_boot
Extracts bootstrap results for a specific iterationextract_boot
Asymptotic variance of gaugegauge_avar
Asymptotic covariance of gaugegauge_covar
Random data of 2SLS model (Monte Carlo)generate_data
Parameters of 2SLS model (Monte Carlo)generate_param
Global test correcting for multiple hypothesis testingglobaltest
Impulse Indicator Saturation (IIS initial estimator)iis_init
Monte Carlo simulations parameter gridmc_grid
Multiple models, varying cut-offmulti_cutoff
Multivariate normal supremum simulationmvn_sup
Create indices for nonparametric bootstrapnonparametric
Nonparametric resampling from a data framenonparametric_resampling
Outlier history of single observationoutlier
Outlier detection algorithmsoutlier_detection
Number of outliersoutliers
Proportion of outliersoutliers_prop
Plotting of standardised residuals and outliersplot.robust2sls
Helper of robust2sls classprint.robust2sls
Proportion testproptest
Robustified 2SLS (full sample initial estimator)robustified_init
Saturated 2SLS (split-sample initial estimator)saturated_init
Create selection (non-outlying) vector from IIS modelselection_iis
Scaling sum proportion test across different cut-offssumtest
Supremum proportion test across different cut-offssuptest
User-specified initial estimatoruser_init
Validator of robust2sls classvalidate_robust2sls
Calculate varrho coefficientsvarrho