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 . 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) .


Reference manual

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install.packages("SCDA")

0.0.2 by Paolo Maranzano, 2 years ago


Browse source code at https://github.com/cran/SCDA


Authors: Paolo Maranzano [aut, cre, cph] , Raffaele Mattera [aut, cph] , Camilla Lionetti [aut, cph] , Francesco Caccia [aut, cph]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports spatialreg, sp, spdep, utils, rlang, performance, stats, methods, dplyr, sf, NbClust, ggplot2, ggspatial

Suggests tidyverse


See at CRAN