spldv: Spatial Models for Limited Dependent Variables

The current version of this package estimates spatial autoregressive models for binary dependent variables using GMM estimators. 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.

Version: 0.1.1
Depends: R (≥ 4.0)
Imports: Formula, Matrix, maxLik, stats, sphet, memisc, car, methods, numDeriv, MASS, spatialreg
Suggests: spdep
Published: 2022-05-09
Author: Mauricio Sarrias ORCID iD [aut, cre], Gianfranco Piras ORCID iD [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
Materials: NEWS
CRAN checks: spldv results

Documentation:

Reference manual: spldv.pdf

Downloads:

Package source: spldv_0.1.1.tar.gz
Windows binaries: r-devel: spldv_0.1.1.zip, r-release: spldv_0.1.1.zip, r-oldrel: spldv_0.1.1.zip
macOS binaries: r-release (arm64): spldv_0.1.1.tgz, r-oldrel (arm64): spldv_0.1.1.tgz, r-release (x86_64): spldv_0.1.1.tgz, r-oldrel (x86_64): spldv_0.1.1.tgz
Old sources: spldv archive

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