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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 |
| 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:
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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