Learn R Programming

SCDA (version 0.0.1)

Spatially-Clustered Data Analysis

Description

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).

Copy Link

Version

Install

install.packages('SCDA')

Monthly Downloads

560

Version

0.0.1

License

GPL (>= 2)

Maintainer

Paolo Maranzano

Last Published

October 14th, 2024

Functions in SCDA (0.0.1)

SpatReg_Extract

Extracts numerical values for the estimated regression parameters (i.e., spatial coefficients, regression coefficients, and residuals variance) for a given spatial regression model of class lm or Sarlm.
SpatReg_PseudoR2

Computes the Pseudo R\(^2\) metric for a given spatial regression model of class lm or Sarlm.
listW

List of 222 spatial weights (style = "W", zero.policy=TRUE) used in Cerqueti, R., Maranzano, P. & Mattera, R. "Spatially-clustered spatial autoregressive models with application to agricultural market concentration in Europe". arXiv preprints (<https://doi.org/10.48550/arXiv.2407.15874>)
SpatReg_Perf

Computes a set of in-sample performance metrics (i.e., AIC, BIC, RMSE, Sigma, and Pseudo R\(^2\)) for a given spatial regression model of class lm or Sarlm.
SCSR_InfoCrit

Automatically select the optimal number of clusters based on likelihood information criteria (i.e., AIC, BIC and HQC) for a given SCSR model.
SCSR_Estim

Estimate spatially-clustered spatial regression models
Elbow_finder

Automatically selects the optimal number of clusters based on elbow criterion.
SpatReg_GoF

Computes a set of goodness-of-fit indices (e.g., likelihood-based information criteria, Wald and LR test, Moran's I statistic) for a given spatial regression model of class lm or Sarlm.
Data2020

Spatial dataset to replicate the results for 2020 from Cerqueti, R., Maranzano, P. & Mattera, R. "Spatially-clustered spatial autoregressive models with application to agricultural market concentration in Europe". arXiv preprints (<https://doi.org/10.48550/arXiv.2407.15874>)
Data2010

Spatial dataset to replicate the results for 2010 from Cerqueti, R., Maranzano, P. & Mattera, R. "Spatially-clustered spatial autoregressive models with application to agricultural market concentration in Europe". arXiv preprints (<https://doi.org/10.48550/arXiv.2407.15874>