Package: sphet 2.0.6
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:
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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
- 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
Last updated 4 months agofrom:bd8dd47dde. Checks:ERROR: 1 NOTE: 2 OK: 4. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | FAIL | Nov 07 2024 |
R-4.5-win | NOTE | Nov 07 2024 |
R-4.5-linux | NOTE | Nov 07 2024 |
R-4.4-win | OK | Nov 07 2024 |
R-4.4-mac | OK | Nov 07 2024 |
R-4.3-win | OK | Nov 07 2024 |
R-4.3-mac | OK | Nov 07 2024 |
Exports:circulardistancegstslshetimpactskpjtestlistw2dgCMatrixread.gwt2distspregstslshac
Dependencies:bootclassclassIntclicodacodetoolsDBIdeldire1071glueKernSmoothlatticeLearnBayeslifecyclemagrittrMASSMatrixmultcompmvtnormnlmeproxyRcpprlangs2sandwichsfspspatialregspDataspdepstringistringrsurvivalTH.dataunitsvctrswkzoo
sphet: Spatial Models with Heteroskedastic Innovations
Rendered fromsphet.Rnw
usingutils::Sweave
on Nov 07 2024.Last update: 2024-02-07
Started: 2013-10-27