spatialreg: Spatial Regression Analysis

A collection of all the estimation functions for spatial cross-sectional models (on lattice/areal data using spatial weights matrices) contained up to now in 'spdep', 'sphet' and 'spse'. These model fitting functions include maximum likelihood methods for cross-sectional models proposed by 'Cliff' and 'Ord' (1973, ISBN:0850860369) and (1981, ISBN:0850860814), fitting methods initially described by 'Ord' (1975) <doi:10.1080/01621459.1975.10480272>. The models are further described by 'Anselin' (1988) <doi:10.1007/978-94-015-7799-1>. Spatial two stage least squares and spatial general method of moment models initially proposed by 'Kelejian' and 'Prucha' (1998) <doi:10.1023/A:1007707430416> and (1999) <doi:10.1111/1468-2354.00027> are provided. Impact methods and MCMC fitting methods proposed by 'LeSage' and 'Pace' (2009) <doi:10.1201/9781420064254> are implemented for the family of cross-sectional spatial regression models. Methods for fitting the log determinant term in maximum likelihood and MCMC fitting are compared by 'Bivand et al.' (2013) <doi:10.1111/gean.12008>, and model fitting methods by 'Bivand' and 'Piras' (2015) <doi:10.18637/jss.v063.i18>; both of these articles include extensive lists of references. 'spatialreg' >= 1.1-* corresponded to 'spdep' >= 1.1-1, in which the model fitting functions were deprecated and passed through to 'spatialreg', but masked those in 'spatialreg'. From versions 1.2-*, the functions have been made defunct in 'spdep'.

Version: 1.2-3
Depends: R (≥ 3.3.0), spData, Matrix, sf
Imports: spdep, expm, coda, methods, MASS, boot, splines, LearnBayes, nlme, gmodels
Suggests: parallel, RSpectra, tmap, foreign, spam, knitr, lmtest, sandwich, rmarkdown, igraph
Published: 2022-04-18
Author: Roger Bivand ORCID iD [cre, aut], Gianfranco Piras [aut], Luc Anselin [ctb], Andrew Bernat [ctb], Eric Blankmeyer [ctb], Yongwan Chun [ctb], Virgilio Gómez-Rubio [ctb], Daniel Griffith [ctb], Martin Gubri [ctb], Rein Halbersma [ctb], James LeSage [ctb], Angela Li [ctb], Hongfei Li [ctb], Jielai Ma [ctb], Abhirup Mallik [ctb, trl], Giovanni Millo [ctb], Kelley Pace [ctb], Pedro Peres-Neto [ctb], Tobias Rüttenauer [ctb], Mauricio Sarrias [ctb], JuanTomas Sayago [ctb], Michael Tiefelsdorf [ctb]
Maintainer: Roger Bivand <Roger.Bivand at nhh.no>
BugReports: https://github.com/r-spatial/spatialreg/issues/
License: GPL-2
URL: https://github.com/r-spatial/spatialreg/, https://r-spatial.github.io/spatialreg/
NeedsCompilation: yes
Citation: spatialreg citation info
Materials: NEWS
In views: Econometrics, Spatial
CRAN checks: spatialreg results

Documentation:

Reference manual: spatialreg.pdf
Vignettes: Moran Eigenvectors
Spatial weights objects as sparse matrices and graphs
Introduction to the North Carolina SIDS data set (re-revised)

Downloads:

Package source: spatialreg_1.2-3.tar.gz
Windows binaries: r-devel: spatialreg_1.2-3.zip, r-release: spatialreg_1.2-3.zip, r-oldrel: spatialreg_1.2-3.zip
macOS binaries: r-release (arm64): spatialreg_1.2-3.tgz, r-oldrel (arm64): spatialreg_1.2-3.tgz, r-release (x86_64): spatialreg_1.2-3.tgz, r-oldrel (x86_64): spatialreg_1.2-3.tgz
Old sources: spatialreg archive

Reverse dependencies:

Reverse depends: GWmodel, lagsarlmtree, spatialprobit, SpatialRegimes, ssfa
Reverse imports: bigDM, FlexScan, latticeDensity, mclcar, pspatreg, sphet, spldv, splm, spqdep, spsur
Reverse suggests: broom, prabclus, spData, spdep
Reverse enhances: MuMIn, texreg

Linking:

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