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 Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=spldv to link to this page.
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