Package: sphet 2.1-1

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.

Authors:Gianfranco Piras [aut, cre], Roger Bivand [ctb]

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sphet.pdf |sphet.html✨
sphet/json (API)

# Install 'sphet' in R:
install.packages('sphet', repos = c('https://gpiras.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/gpiras/sphet/issues

Datasets:
  • coldis - Object of class distance for Columbus dataset 10-nearest neighbors matrix for columbus dataset
  • knn10columbus - Object of class distance for Columbus dataset 10-nearest neighbors matrix for columbus dataset

On CRAN:

Conda:

7.43 score 8 stars 3 packages 188 scripts 635 downloads 1 mentions 9 exports 38 dependencies

Last updated 18 days agofrom:6b276d9a62. Checks:1 ERROR, 8 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesFAILMar 10 2025
R-4.5-winOKMar 10 2025
R-4.5-macOKMar 10 2025
R-4.5-linuxOKMar 10 2025
R-4.4-winOKMar 10 2025
R-4.4-macOKMar 10 2025
R-4.4-linuxOKMar 10 2025
R-4.3-winOKMar 10 2025
R-4.3-macOKMar 10 2025

Exports:circulardistancegstslshetimpactskpjtestlistw2dgCMatrixread.gwt2distspregstslshac

Dependencies:bootclassclassIntclicodacodetoolsDBIdeldire1071glueKernSmoothlatticeLearnBayeslifecyclemagrittrMASSMatrixmultcompmvtnormnlmeproxyRcpprlangs2sandwichsfspspatialregspDataspdepstringistringrsurvivalTH.dataunitsvctrswkzoo

sphet: Spatial Models with Heteroskedastic Innovations

Rendered fromsphet.Rnwusingutils::Sweaveon Mar 10 2025.

Last update: 2024-02-07
Started: 2013-10-27