Package: ssmrob 1.0

Mikhail Zhelonkin

ssmrob: Robust Estimation and Inference in Sample Selection Models

Package provides a set of tools for robust estimation and inference for models with sample selectivity and endogenous treatment model. For details, see Zhelonkin and Ronchetti (2021) <doi:10.18637/jss.v099.i04>.

Authors:Mikhail Zhelonkin, Marc G. Genton, Elvezio Ronchetti

ssmrob_1.0.tar.gz
ssmrob_1.0.tar.gz(r-4.5-noble)ssmrob_1.0.tar.gz(r-4.4-noble)
ssmrob_1.0.tgz(r-4.4-emscripten)ssmrob_1.0.tgz(r-4.3-emscripten)
ssmrob.pdf |ssmrob.html✨
ssmrob/json (API)
NEWS

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

Peer review:

Datasets:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

14 exports 0.00 score 72 dependencies 10 scripts 359 downloads

Last updated 3 years agofrom:e91bed9355. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 19 2024
R-4.5-linuxOKAug 19 2024

Exports:dLambdadSMdLambdadSM5etreg2steprobVcovetregrobheck2steprobVcovheck5twosteprobVcovheckit5robheckitrobheckitrob.controlMmatrMPsiMestssmrobx2weight.covMcdx2weight.robCov

Dependencies:abindbackportsbootbroomcarcarDataclicolorspacecowplotcpp11DEoptimRDerivdigestdoBydplyrfansifarverFormulagenericsggplot2gluegtableisobandlabelinglatticelifecyclelme4lmtestmagrittrMASSMatrixMatrixModelsmaxLikmgcvmicrobenchmarkminqamiscToolsmodelrmunsellmvtnormnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigpurrrquantregR6RColorBrewerRcppRcppEigenrlangrobustbasesampleSelectionsandwichscalesSparseMstringistringrsurvivalsystemfittibbletidyrtidyselectutf8vctrsVGAMviridisLitewithrzoo

Readme and manuals

Help Manual

Help pageTopics
Robust Estimation and Inference in Sample Selection Modelsssmrob-package
Extract Coefficients from Robust Endogenous Treatment Model Fitcoef.etregrob
Extract Coefficients from Robust Sample Selection Model Fitcoef.heckit5rob
Extract Coefficients from Robust Sample Selection Model Fitcoef.heckitrob
Inverse Mills Ratio DerivativedLambdadSM
Inverse Mills Ratio DerivativedLambdadSM5
Variance Covariance Matrixetreg2steprobVcov
Robust Fit of Endogenous Treatment Modeletregrob
Fitted values of endogenous treatment modelfitted.etregrob
Fitted values of robust sample selection modelfitted.heckit5rob
Fitted values of robust sample selection modelfitted.heckitrob
Variance Covariance Matrixheck2steprobVcov
Variance Covariance Matrixheck5twosteprobVcov
Robust Heckit Fit: Switching Regressionsheckit5rob
Robust Heckit Fitheckitrob
Auxiliary for Controlling Robust Fittingheckitrob.control
Ambulatory Expenditures DataMEPS2001
M MatrixMmatrM
Design Matrix of Endogenous Treatment Modelmodel.matrix.etregrob
Design Matrix of Switching Regression Modelmodel.matrix.heckit5rob
Design Matrix of Sample Selection Modelmodel.matrix.heckitrob
Wage Offer DataMROZ.RAW
Number of Observationsnobs.etregrob nobs.heckit5rob nobs.heckitrob
Print a 'etregrob' Objectprint.etregrob
Print a 'heckit5rob' Objectprint.heckit5rob
Print a 'heckitrob' Objectprint.heckitrob
Print Function for 'summary.etregrob'print.summary.etregrob
Print Function for 'summary.heckit5rob'print.summary.heckit5rob
Print Function for 'summary.heckitrob'print.summary.heckitrob
Score Function of the Mallows M-EstimatorPsiMest
Residuals of Robust Endogenous Treatment Model Fitresiduals.etregrob
Residuals of Robust Sample Selection Model Fitresiduals.heckit5rob
Residuals of Robust Sample Selection Model Fitresiduals.heckitrob
Robust Sample Selection Modelssmrob
Summarizing Robust Fits of Endogenous Treatment Modelssummary.etregrob
Summarizing Robust Fits of Sample Selection Modelssummary.heckit5rob
Summarizing Robust Fits of Sample Selection Modelssummary.heckitrob
Extract Asymptotic Variance Covariance Matrixvcov.etregrob
Extract Asymptotic Variance Covariance Matrixvcov.heckit5rob
Extract Asymptotic Variance Covariance Matrixvcov.heckitrob
Robustness Weightsx2weight.covMcd
Robustness Weightsx2weight.robCov