Geoadditive Small Area Estimation for Area-Level Model R package geoaddSAE2 version 0.1.1 Fits area-level geoadditive small area estimation (SAE) models by extending the Fay-Herriot area-level model with linear, nonlinear, and spatial effects. The Fay-Herriot model is described by Fay and Herriot (1979) <doi:10.1080/01621459.1979.10482505>. Geoadditive models combine nonlinear covariate effects and spatial variation as described by Kammann and Wand (2003) <doi:10.1111/1467-9876.00385>, while their application to small area estimation is discussed by Pusponegoro et al. (2019) <doi:10.21108/JDSA.2019.2.15>. Nonlinear covariate effects are represented using penalized splines, while spatial effects are represented using a smooth function of geographic coordinates. Models are estimated using restricted maximum likelihood (REML), and mean squared error (MSE) is estimated using a parametric bootstrap. The package also provides comparisons with the Fay-Herriot and spatial Fay-Herriot (SFH) models. Software Depends: R (>= 3.5.0) Imports: mgcv, sae, stats Suggests: knitr, rmarkdown, testthat (>= 3.0.0) Amalyah Rizky Khairunnisa Sutarto <222212489@stis.ac.id> Comprehensive R Archive Network (CRAN) Amalyah Rizky Khairunnisa Sutarto [aut, cre], Novi Hidayat Pusponegoro [aut, ths] GPL (>= 3) 2026-10-05 application/tgz https://CRAN.R-project.org/package=geoaddSAE2 doi:10.32614/CRAN.package.geoaddSAE2