Package: spatialreg 1.3-6

Roger Bivand

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'. 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. A recent review is provided by 'Bivand', 'Millo' and 'Piras' (2021) <doi:10.3390/math9111276>. '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'. From version 1.3-6, add Anselin-Kelejian (1997) test to `stsls` for residual spatial autocorrelation <doi:10.1177/016001769702000109>.

Authors:Roger Bivand [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], Josiah Parry [ctb], Pedro Peres-Neto [ctb], Tobias Rüttenauer [ctb], Mauricio Sarrias [ctb], JuanTomas Sayago [ctb], Michael Tiefelsdorf [ctb]

spatialreg_1.3-6.tar.gz
spatialreg_1.3-6.tar.gz(r-4.5-noble)spatialreg_1.3-6.tar.gz(r-4.4-noble)
spatialreg_1.3-6.tgz(r-4.4-emscripten)spatialreg_1.3-6.tgz(r-4.3-emscripten)
spatialreg.pdf |spatialreg.html
spatialreg/json (API)
NEWS

# Install 'spatialreg' in R:
install.packages('spatialreg', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/r-spatial/spatialreg/issues

Pkgdown:https://r-spatial.github.io

Uses libs:
  • openblas– Optimized BLAS

openblas

8.61 score 22 packages 712 scripts 9.6k downloads 6 mentions 80 exports 30 dependencies

Last updated 8 days agofrom:f36e19f1f5. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKDec 02 2024
R-4.5-linux-x86_64OKDec 02 2024

Exports:apleaple.mcaple.plotas_dgRMatrix_listwas_dsCMatrix_Ias_dsCMatrix_IrWas_dsTMatrix_listwas.spam.listwbptest.Sarlmcan.be.simmedcheb_setupcoercecreate_WXdo_ldeteigen_pre_setupeigen_setupeigenwerrorsarlmget.ClusterOptionget.coresOptionget.mcOptionget.VerboseOptionget.ZeroPolicyOptionGMargminImageGMerrorsargriffith_sonegstslsHausman.testimpactsintImpactsinvIrMinvIrWJacobian_WjacobianSetupl_maxlagmesslagsarlmlextrBlextrSlextrWlistw2U_Matrixlistw2U_spamlmSLXlocalApleLR.SarlmLR1.LagmessLR1.SarlmLR1.SpautolmLU_prepermutate_setupLU_setupMatrix_J_setupMatrix_setupmcdet_setupMCMCsampMEmom_calcmom_calc_int2moments_setuppowerWeightssacsarlmSE_classic_setupSE_interp_setupSE_whichMin_setupset.ClusterOptionset.coresOptionset.mcOptionset.VerboseOptionset.ZeroPolicyOptionsimilar.listwspam_setupspam_update_setupSpatialFilteringspautolmspBreg_errspBreg_lagspBreg_sacstslssubgraph_eigenwtrWWald1.Sarlm

Dependencies:bootclassclassIntcodacodetoolsDBIdeldire1071KernSmoothlatticeLearnBayesmagrittrMASSMatrixmultcompmvtnormnlmeproxyRcpps2sandwichsfspspDataspdepsurvivalTH.dataunitswkzoo

North Carolina SIDS data set (models)

Rendered fromsids_models.Rmdusingknitr::rmarkdownon Dec 02 2024.

Last update: 2024-08-20
Started: 2019-04-01

Moran Eigenvectors

Rendered fromSpatialFiltering.Rmdusingknitr::rmarkdownon Dec 02 2024.

Last update: 2024-06-11
Started: 2019-04-01

Spatial weights objects as sparse matrices and graphs

Rendered fromnb_igraph.Rmdusingknitr::rmarkdownon Dec 02 2024.

Last update: 2024-08-20
Started: 2021-11-11

Readme and manuals

Help Manual

Help pageTopics
Approximate profile-likelihood estimator (APLE)aple
Approximate profile-likelihood estimator (APLE) permutation testaple.mc
Approximate profile-likelihood estimator (APLE) scatterplotaple.plot localAple
Spatial neighbour sparse representationas.spam.listw as_dgRMatrix_listw as_dsCMatrix_I as_dsCMatrix_IrW as_dsTMatrix_listw coerce,listw,CsparseMatrix-method coerce,listw,RsparseMatrix-method coerce,listw,symmetricMatrix-method Jacobian_W listw2U_Matrix listw2U_spam powerWeights
Spatial regression model Jacobian computationscan.be.simmed cheb_setup do_ldet eigen_pre_setup eigen_setup jacobianSetup LU_prepermutate_setup LU_setup Matrix_J_setup Matrix_setup mcdet_setup moments_setup SE_classic_setup SE_interp_setup SE_whichMin_setup spam_setup spam_update_setup
Spatial simultaneous autoregressive error model estimation by GMMcoef.Gmsar deviance.Gmsar fitted.Gmsar GMargminImage GMerrorsar Hausman.test.Gmsar print.Gmsar print.summary.Gmsar residuals.Gmsar summary.Gmsar
Spatial weights matrix eigenvalueseigenw griffith_sone subgraph_eigenw
Spatial simultaneous autoregressive SAC model estimation by GMMgstsls impacts.Gmsar
Impacts in spatial lag modelsHPDinterval.LagImpact impacts intImpacts plot.LagImpact print.LagImpact print.summary.LagImpact summary.LagImpact
Compute SAR generating operatorinvIrM invIrW
Matrix exponential spatial lag modelcoef.Lagmess deviance.Lagmess fitted.Lagmess impacts.Lagmess lagmess logLik.Lagmess LR1.Lagmess print.Lagmess print.summary.Lagmess residuals.Lagmess summary.Lagmess
Find extreme eigenvalues of binary symmetric spatial weightslextrB lextrS lextrW l_max
Spatial Durbin linear (SLX, spatially lagged X) modelcreate_WX impacts.SlX lmSLX predict.SlX print.SlX print.summary.SlX print.summary.WXimpact print.WXimpact summary.SlX summary.WXimpact
Likelihood ratio testanova.Sarlm bptest.Sarlm Hausman.test Hausman.test.Sarlm impacts.Sarlm logLik.Sarlm LR.Sarlm LR1.Sarlm Wald1.Sarlm
MCMC sample from fitted spatial regressionMCMCsamp MCMCsamp.Sarlm MCMCsamp.Spautolm
Moran eigenvector GLM filteringfitted.Me_res ME print.Me_res
Spatial simultaneous autoregressive model estimation by maximum likelihoodcoef.Sarlm deviance.Sarlm errorsarlm fitted.Sarlm lagsarlm print.Sarlm print.summary.Sarlm residuals.Sarlm sacsarlm summary.Sarlm vcov.Sarlm
Prediction for spatial simultaneous autoregressive linear model objectsas.data.frame.Sarlm.pred predict.Sarlm print.Sarlm.pred
Options for parallel supportget.ClusterOption get.coresOption get.mcOption set.ClusterOption set.coresOption set.mcOption
Control checking of spatial object IDsget.VerboseOption get.ZeroPolicyOption set.VerboseOption set.ZeroPolicyOption
Create symmetric similar weights listssimilar.listw
Semi-parametric spatial filteringfitted.SfResult print.SfResult SpatialFiltering
Spatial conditional and simultaneous autoregression model estimationcoef.Spautolm deviance.Spautolm fitted.Spautolm logLik.Spautolm LR1.Spautolm print.Spautolm print.summary.Spautolm residuals.Spautolm spautolm summary.Spautolm
Bayesian MCMC spatial simultaneous autoregressive model estimationimpacts.MCMC_sac_G impacts.MCMC_sar_G impacts.MCMC_sem_G spBreg_err spBreg_lag spBreg_sac
Generalized spatial two stage least squarescoef.Stsls deviance.Stsls impacts.Stsls print.Stsls print.summary.Stsls residuals.Stsls stsls summary.Stsls
Spatial weights matrix powers tracesmom_calc mom_calc_int2 trW