Package: ssmodels 1.0.1
ssmodels: Sample Selection Models
In order to facilitate the adjustment of the sample selection models existing in the literature, we created the 'ssmodels' package. Our package allows the adjustment of the classic Heckman model (Heckman (1976), Heckman (1979) <doi:10.2307/1912352>), and the estimation of the parameters of this model via the maximum likelihood method and two-step method, in addition to the adjustment of the Heckman-t models, introduced in the literature by Marchenko and Genton (2012) <doi:10.1080/01621459.2012.656011> and the Heckman-Skew model introduced in the literature by Ogundimu and Hutton (2016) <doi:10.1111/sjos.12171>. We also implemented functions to adjust the generalized version of the Heckman model, introduced by Bastos, Barreto-Souza, and Genton (2021) <doi:10.5705/ss.202021.0068>, that allows the inclusion of covariables to the dispersion and correlation parameters and a function to adjust the Heckman-BS model introduced by Bastos and Barreto-Souza (2020) <doi:10.1080/02664763.2020.1780570> that uses the Birnbaum-Saunders distribution as a joint distribution of the selection and primary regression variables.
Authors:
ssmodels_1.0.1.tar.gz
ssmodels_1.0.1.zip(r-4.5)ssmodels_1.0.1.zip(r-4.4)ssmodels_1.0.1.zip(r-4.3)
ssmodels_1.0.1.tgz(r-4.4-any)ssmodels_1.0.1.tgz(r-4.3-any)
ssmodels_1.0.1.tar.gz(r-4.5-noble)ssmodels_1.0.1.tar.gz(r-4.4-noble)
ssmodels_1.0.1.tgz(r-4.4-emscripten)ssmodels_1.0.1.tgz(r-4.3-emscripten)
ssmodels.pdf |ssmodels.html✨
ssmodels/json (API)
NEWS
| # Install 'ssmodels' in R: |
| install.packages('ssmodels', repos = c('https://fsbmat-ufv.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/fsbmat-ufv/ssmodels/issues
Last updated 2 years agofrom:f876017c28. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Aug 27 2024 |
| R-4.5-win | OK | Aug 27 2024 |
| R-4.5-linux | OK | Aug 27 2024 |
| R-4.4-win | OK | Aug 27 2024 |
| R-4.4-mac | OK | Aug 27 2024 |
| R-4.3-win | OK | Aug 27 2024 |
| R-4.3-mac | OK | Aug 27 2024 |
Exports:HCinitialHeckmanBSHeckmanCLHeckmanGeHeckmanSKHeckmantSIMRstep2summary.HeckmanBSsummary.HeckmanCLsummary.HeckmanGesummary.HeckmanSKsummary.HeckmantStwostep
Dependencies:digestlatticeMASSMatrixMatrixModelsmiscToolsmnormtnumDerivpracmaquantregrbibutilsRdpacksnSparseMsurvival
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Two-Step Method for Parameter Estimation of the Heckman Model | HCinitial |
| Heckman BS Model fit Function | HeckmanBS |
| Classic Heckman Model fit Function | HeckmanCL |
| Function for fit of the Generalized Heckman Model | HeckmanGe |
| Normal Skew Model fit Function | HeckmanSK |
| Heckman-t Model fit Function | HeckmantS |
| Inverse Mills Ratio | IMR |
| Medical Expenditure Panel Survey | MEPS2001 |
| U.S. Women's Labor Force Participation | Mroz87 |
| US National Health and Nutrition Examination Study | nhanes |
| Panel Study of Income Dynamics | PSID2 |
| RAND Health Insurance Experiment | RandHIE |
| ssmodels: A package for fit the sample selection models. | ssmodels |
| Heckman's two-step method | step2 |
| Summary of Birnbaum-Saunders Heckman Model | summary.HeckmanBS |
| Summary of Classic Heckman Model | summary.HeckmanCL |
| Summary of Generalized Heckman Model | summary.HeckmanGe |
| Summary of Skew-Normal Heckman Model | summary.HeckmanSK |
| Summary of Heckman-ts Model | summary.HeckmantS |
| Heckman's two-step method | twostep |
