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spsur

swMATH ID: 44232
Software Authors: Angulo, Ana; Lopez, Fernando A; Minguez, Roman; Mur, Jesus
Description: R package spsur: Spatial Seemingly Unrelated Regression Models. A collection of functions to test and estimate Seemingly Unrelated Regression (usually called SUR) models, with spatial structure, by maximum likelihood and three-stage least squares. The package estimates the most common spatial specifications, that is, SUR with Spatial Lag of X regressors (called SUR-SLX), SUR with Spatial Lag Model (called SUR-SLM), SUR with Spatial Error Model (called SUR-SEM), SUR with Spatial Durbin Model (called SUR-SDM), SUR with Spatial Durbin Error Model (called SUR-SDEM), SUR with Spatial Autoregressive terms and Spatial Autoregressive Disturbances (called SUR-SARAR), SUR-SARAR with Spatial Lag of X regressors (called SUR-GNM) and SUR with Spatially Independent Model (called SUR-SIM). The methodology of these models can be found in next references Minguez, R., Lopez, F.A., and Mur, J. (2022) <doi:10.18637/jss.v104.i11> Mur, J., Lopez, F.A., and Herrera, M. (2010) <doi:10.1080/17421772.2010.516443> Lopez, F.A., Mur, J., and Angulo, A. (2014) <doi:10.1007/s00168-014-0624-2>.
Homepage: https://cran.r-project.org/web/packages/spsur/index.html
Source Code:  https://github.com/cran/spsur
Dependencies: R
Keywords: Journal of Statistical Software; R package; R; spatial seemingly unrelated regression models; Lagrange multipliers test; maximum likelihood; instrumental variables; panel data; COVID-19; mobility
Related Software: splm; spatialreg; sphet; spdep; R; car; memisc; spmat; spData; Matrix; R-INLA; ProbitSpatial; spatialprobit; McSpatial; spldv; Pysal; SpaceStat; spse; Systemfit; sf
Cited in: 0 Documents

Standard Articles

1 Publication describing the Software Year
spsur: An R Package for Dealing with Spatial Seemingly Unrelated Regression Models Link
Ana Angulo, Fernando A Lopez, Roman Minguez, Jesus Mur
2022