Coarse-to-Fine Spatial Modeling R package spCF version 0.1.2 Provides functions for coarse-to-fine spatial modeling (CFSM), enabling fast spatial prediction, regression, and uncertainty quantification. This method is suitable for moderate to large samples. For methodological details, see Murakami et al. (2026) <doi:10.1111/gean.70034> and related works on its generalized-linear <doi:10.48550/arXiv.2605.01157> and downscaling extensions. Software Imports: FNN, fields, nloptr, dbscan, ranger, withr, Rcpp LinkingTo: Rcpp Suggests: sp, sf, knitr, rmarkdown, CARBayesdata, lightgbm Daisuke Murakami <dmuraka@ism.ac.jp> Comprehensive R Archive Network (CRAN) Daisuke Murakami [aut, cre], Alexis Comber [aut], Takahiro Yoshida [aut], Narumasa Tsutsumida [aut], Chris Brunsdon [aut], Tomoki Nakaya [aut] GPL (>= 2) 2026-06-29 application/tgz https://CRAN.R-project.org/package=spCF doi:10.32614/CRAN.package.spCF