Spatially-Clustered Data Analysis R package SCDA version 0.0.2 Contains functions for statistical data analysis based on spatially-clustered techniques. The package allows estimating the spatially-clustered spatial regression models presented in Cerqueti, Maranzano \& Mattera (2024), "Spatially-clustered spatial autoregressive models with application to agricultural market concentration in Europe", arXiv preprint 2407.15874 <doi:10.48550/arXiv.2407.15874>. Specifically, the current release allows the estimation of the spatially-clustered linear regression model (SCLM), the spatially-clustered spatial autoregressive model (SCSAR), the spatially-clustered spatial Durbin model (SCSEM), and the spatially-clustered linear regression model with spatially-lagged exogenous covariates (SCSLX). From release 0.0.2, the library contains functions to estimate spatial clustering based on Adiajacent Matrix K-Means (AMKM) as described in Zhou, Liu \& Zhu (2019), "Weighted adjacent matrix for K-means clustering", Multimedia Tools and Applications, 78 (23) <doi:10.1007/s11042-019-08009-x>. Software Depends: R (>= 3.5.0) Imports: spatialreg,sp,spdep,utils,rlang,performance,stats,methods,dplyr,sf,NbClust,ggplot2,ggspatial Suggests: tidyverse, Paolo Maranzano <pmaranzano.ricercastatistica@gmail.com> Comprehensive R Archive Network (CRAN) Paolo Maranzano [aut, cre, cph] (ORCID: <https://orcid.org/0000-0002-9228-2759>), Raffaele Mattera [aut, cph] (ORCID: <https://orcid.org/0000-0001-8770-7049>), Camilla Lionetti [aut, cph], Francesco Caccia [aut, cph] GPL (>= 2) 2024-10-22 application/tgz https://CRAN.R-project.org/package=SCDA doi:10.32614/CRAN.package.SCDA en-US