spldv: Spatial Models for Limited Dependent Variables
The current version of this package estimates spatial autoregressive models for binary dependent variables using GMM estimators <doi:10.18637/jss.v107.i08>. It supports one-step (Pinkse and Slade, 1998) <doi:10.1016/S0304-4076(97)00097-3> and two-step GMM estimator along with the linearized GMM estimator proposed by Klier and McMillen (2008) <doi:10.1198/073500107000000188>. It also allows for either Probit or Logit model and compute the average marginal effects. All these models are presented in Sarrias and Piras (2023) <doi:10.1016/j.jocm.2023.100432>.
| Version: | 0.1.3 |
| Depends: | R (≥ 4.0) |
| Imports: | Formula,Matrix,maxLik, stats,sphet,memisc,car, methods,numDeriv,MASS,spatialreg |
| Suggests: | spdep |
| Published: | 2023-10-11 |
| DOI: | 10.32614/CRAN.package.spldv |
| Author: | Mauricio Sarrias [aut, cre], Gianfranco Piras [aut], Daniel McMillen [ctb] |
| Maintainer: | Mauricio Sarrias <msarrias86 at gmail.com> |
| BugReports: | https://github.com/gpiras/spldv/issues |
| License: | GPL-2 |GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | https://github.com/gpiras/spldv |
| NeedsCompilation: | no |
| Citation: | spldv citation info |
| Materials: | NEWS |
| CRAN checks: | spldv results |
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