spboost: Gradient Boosting for Nonlinear Spatial Autoregressive Models
Flexible nonlinear extension of spatial autoregressive (SAR),
spatial error (SEM), and spatial autoregressive with autoregressive
disturbances (SARAR) models with multiple regression engines
(generalized additive models ('mgcv'), gradient boosting ('mboost'),
multivariate adaptive regression splines ('earth'), and 'xgboost')
and two families of spatial-parameter estimators: maximum likelihood
and the determinant-free Closed-Form Estimator of Smirnov (2020)
<doi:10.1111/gean.12268>. See Geniaux G. (2026). "Flexible nonlinear
spatial autoregressive models: a gradient boosting approach with
closed-form estimation." Presented at Spatial Econometrics World
Congress (SEA/SEW 2026, Paris), unpublished.
| Version: |
0.7.0 |
| Depends: |
Matrix, mboost, mgcv, methods, mgwrsar |
| Imports: |
Rcpp, sf, MASS, data.table, xgboost, caret, doParallel, foreach, nabor, earth |
| LinkingTo: |
RcppEigen, Rcpp |
| Suggests: |
blockCV, knitr, rmarkdown, RSpectra, spatialreg, spdep, testthat (≥ 3.0.0) |
| Published: |
2026-06-08 |
| DOI: |
10.32614/CRAN.package.spboost (may not be active yet) |
| Author: |
Ghislain Geniaux [aut, cre] |
| Maintainer: |
Ghislain Geniaux <ghislain.geniaux at inrae.fr> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
yes |
| CRAN checks: |
spboost results |
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=spboost
to link to this page.