Gradient Boosting for Nonlinear Spatial Autoregressive Models R package spboost version 0.7.0 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 Presented at Spatial Econometrics World Congress (SEA/SEW 2026, Paris), unpublished. Software 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) Ghislain Geniaux <ghislain.geniaux@inrae.fr> Comprehensive R Archive Network (CRAN) Ghislain Geniaux [aut, cre] GPL (>= 2) 2026-06-08 application/tgz https://CRAN.R-project.org/package=spboost doi:10.32614/CRAN.package.spboost