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spboost  

Gradient Boosting for Nonlinear Spatial Autoregressive Models
View on CRAN: Click here


Download and install spboost package within the R console
Install from CRAN:
install.packages("spboost")

Install from Github:
library("remotes")
install_github("cran/spboost")

Install by package version:
library("remotes")
install_version("spboost", "0.7.0")



Attach the package and use:
library("spboost")
Maintained by
Ghislain Geniaux
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-06-08
Latest Update: 2026-06-08
Description:
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 Presented at Spatial Econometrics World Congress (SEA/SEW 2026, Paris), unpublished.
How to cite:
Ghislain Geniaux (2026). spboost: Gradient Boosting for Nonlinear Spatial Autoregressive Models. R package version 0.7.0, https://cran.r-project.org/web/packages/spboost. Accessed 14 Jul. 2026.
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Complete documentation for spboost
Functions, R codes and Examples using the spboost R package
Full spboost package functions and examples
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