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 Presented at Spatial Econometrics World Congress (SEA/SEW 2026, Paris), unpublished.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.7.0 |
rolling linux/jammy R-4.5 | spboost_0.7.0.tar.gz |
884.7 KiB |
0.7.0 |
rolling linux/noble R-4.5 | spboost_0.7.0.tar.gz |
886.9 KiB |
0.7.0 |
rolling source/ R- | spboost_0.7.0.tar.gz |
420.1 KiB |
0.7.0 |
latest linux/jammy R-4.5 | spboost_0.7.0.tar.gz |
884.7 KiB |
0.7.0 |
latest linux/noble R-4.5 | spboost_0.7.0.tar.gz |
886.9 KiB |
0.7.0 |
latest source/ R- | spboost_0.7.0.tar.gz |
420.1 KiB |
0.7.0 |
2026-04-23 source/ R- | spboost_0.7.0.tar.gz |
0 B |