SCDA: Spatially-Clustered Data Analysis
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>.
| Version: | 0.0.2 |
| Depends: | R (≥ 3.5.0) |
| Imports: | spatialreg,sp,spdep, utils,rlang,performance, stats, methods,dplyr,sf,NbClust,ggplot2,ggspatial |
| Suggests: | tidyverse |
| Published: | 2024-10-22 |
| DOI: | 10.32614/CRAN.package.SCDA |
| Author: | Paolo Maranzano [aut, cre, cph], Raffaele Mattera [aut, cph], Camilla Lionetti [aut, cph], Francesco Caccia [aut, cph] |
| Maintainer: | Paolo Maranzano <pmaranzano.ricercastatistica at gmail.com> |
| License: | GPL-2 |GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| Language: | en-US |
| Citation: | SCDA citation info |
| CRAN checks: | SCDA results |
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