sphet: Estimation of Spatial Autoregressive Models with and without Heteroskedastic Innovations

Functions for fitting Cliff-Ord-type spatial autoregressive models with and without heteroskedastic innovations using Generalized Method of Moments estimation are provided. Some support is available for fitting spatial HAC models, and for fitting with non-spatial endogeneous variables using instrumental variables.

Version: 2.0
Depends: R (≥ 3.0.1)
Imports: nlme, spatialreg, spdep, Matrix, sp, methods, stats, utils, mvtnorm, stringr, coda, spData, sf
Published: 2022-01-06
DOI: 10.32614/CRAN.package.sphet
Author: Gianfranco Piras ORCID iD [aut, cre], Roger Bivand ORCID iD [ctb]
Maintainer: Gianfranco Piras <gpiras at mac.com>
BugReports: https://github.com/gpiras/sphet/issues
License: GPL-2
URL: https://github.com/gpiras/sphet
NeedsCompilation: no
Citation: sphet citation info
Materials: README
In views: Econometrics, MixedModels, Spatial, SpatioTemporal
CRAN checks: sphet results


Reference manual: sphet.pdf
Vignettes: sphet: Spatial Models with Heteroskedastic Innovations


Package source: sphet_2.0.tar.gz
Windows binaries: r-devel: sphet_2.0.zip, r-release: sphet_2.0.zip, r-oldrel: sphet_2.0.zip
macOS binaries: r-release (arm64): sphet_2.0.tgz, r-oldrel (arm64): sphet_2.0.tgz, r-release (x86_64): sphet_2.0.tgz, r-oldrel (x86_64): sphet_2.0.tgz
Old sources: sphet archive

Reverse dependencies:

Reverse imports: hspm, spldv, spsur


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