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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>.

Version:1.0.2.6
Depends:R (≥ 4.1), methods (≥ 4.1), stats (≥ 4.1)
Imports:Formula (≥ 1.2-5),ggplot2 (≥ 3.5.2),gmodels (≥ 2.19.1),gridExtra (≥ 2.3),MASS (≥ 7.3-65),Matrix (≥ 1.4-1),minqa (≥ 1.2.8),numDeriv (≥ 2016.8-1.1),Rdpack (≥ 2.6.4),rlang (≥ 1.1.6),sparseMVN (≥ 0.2.2),spatialreg (≥ 1.3-6),spdep (≥ 1.4-1),sphet (≥ 2.1-1)
Suggests:bookdown (≥ 0.44),dplyr (≥ 1.1.4),kableExtra (≥ 1.4.0),knitr (≥ 1.50),rmarkdown (≥ 2.29),sf (≥ 1.0-20)
Published:2025-09-03
DOI:10.32614/CRAN.package.spsur
Author:Ana Angulo [aut], Fernando A Lopez [aut], Roman Minguez [aut, cre], Jesus Mur [aut]
Maintainer:Roman Minguez <roman.minguez at uclm.es>
BugReports:https://github.com/rominsal/spsur/issues
License:GPL-3
URL:https://CRAN.R-project.org/package=spsur
NeedsCompilation:no
Citation:spsur citation info
In views:Econometrics,Spatial
CRAN checks:spsur results

Documentation:

Reference manual:spsur.html ,spsur.pdf
Vignettes:spsur user guide (source)
Maximum Likelihood estimation of Spatial Seemingly Unrelated Regression models. A short Monte Carlo exercise with spsur and spse (source)
spsur vs spatialreg (source)
Spatial seemingly unrelated regression models. A comparison of spsur, spse and PySAL (source)

Downloads:

Package source: spsur_1.0.2.6.tar.gz
Windows binaries: r-devel:spsur_1.0.2.6.zip, r-release:spsur_1.0.2.6.zip, r-oldrel:spsur_1.0.2.6.zip
macOS binaries: r-release (arm64):spsur_1.0.2.6.tgz, r-oldrel (arm64):spsur_1.0.2.6.tgz, r-release (x86_64):spsur_1.0.2.6.tgz, r-oldrel (x86_64):spsur_1.0.2.6.tgz
Old sources: spsur archive

Linking:

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