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:	2.1-1
Depends:	R (≥ 3.0.1)
Imports:	nlme, spatialreg, spdep, Matrix, sp, methods, stats, utils, mvtnorm, stringr, coda, spData (≥ 2.3.1), sf
Published:	2024-12-06
DOI:	10.32614/CRAN.package.sphet
Author:	Gianfranco Piras [aut, cre], Roger Bivand [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

Documentation:

Reference manual:	sphet.html , sphet.pdf
Vignettes:	sphet: Spatial Models with Heteroskedastic Innovations (source, R code)

Downloads:

Package source:	sphet_2.1-1.tar.gz
Windows binaries:	r-devel: sphet_2.1-1.zip, r-release: sphet_2.1-1.zip, r-oldrel: sphet_2.1-1.zip
macOS binaries:	r-release (arm64): sphet_2.1-1.tgz, r-oldrel (arm64): sphet_2.1-1.tgz, r-release (x86_64): sphet_2.1-1.tgz, r-oldrel (x86_64): sphet_2.1-1.tgz
Old sources:	sphet archive

Reverse dependencies:

Reverse imports:	hspm, spldv, spsur
Reverse suggests:	BIDistances

Linking:

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