Package: spatialreg 1.3-5
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'.
Authors:
spatialreg_1.3-5.tar.gz
spatialreg_1.3-5.zip(r-4.5)spatialreg_1.3-5.zip(r-4.4)spatialreg_1.3-5.zip(r-4.3)
spatialreg_1.3-5.tgz(r-4.4-x86_64)spatialreg_1.3-5.tgz(r-4.4-arm64)spatialreg_1.3-5.tgz(r-4.3-x86_64)spatialreg_1.3-5.tgz(r-4.3-arm64)
spatialreg_1.3-5.tar.gz(r-4.5-noble)spatialreg_1.3-5.tar.gz(r-4.4-noble)
spatialreg_1.3-5.tgz(r-4.4-emscripten)spatialreg_1.3-5.tgz(r-4.3-emscripten)
spatialreg.pdf |spatialreg.html✨
spatialreg/json (API)
NEWS
# Install 'spatialreg' in R: |
install.packages('spatialreg', repos = c('https://r-spatial.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/r-spatial/spatialreg/issues
bayesianimpactsmaximum-likelihoodspatial-dependencespatial-econometricsspatial-regression
Last updated 19 days agofrom:93683eddb9. Checks:OK: 9. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Aug 19 2024 |
R-4.5-win-x86_64 | OK | Aug 19 2024 |
R-4.5-linux-x86_64 | OK | Aug 19 2024 |
R-4.4-win-x86_64 | OK | Aug 19 2024 |
R-4.4-mac-x86_64 | OK | Aug 19 2024 |
R-4.4-mac-aarch64 | OK | Aug 19 2024 |
R-4.3-win-x86_64 | OK | Aug 19 2024 |
R-4.3-mac-x86_64 | OK | Aug 19 2024 |
R-4.3-mac-aarch64 | OK | Aug 19 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.Rmd
usingknitr::rmarkdown
on Aug 19 2024.Last update: 2024-08-02
Started: 2019-03-20
Moran Eigenvectors
Rendered fromSpatialFiltering.Rmd
usingknitr::rmarkdown
on Aug 19 2024.Last update: 2024-06-10
Started: 2019-03-20
Spatial weights objects as sparse matrices and graphs
Rendered fromnb_igraph.Rmd
usingknitr::rmarkdown
on Aug 19 2024.Last update: 2024-06-16
Started: 2021-11-10
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Approximate profile-likelihood estimator (APLE) | aple |
Approximate profile-likelihood estimator (APLE) permutation test | aple.mc |
Approximate profile-likelihood estimator (APLE) scatterplot | aple.plot localAple |
Spatial neighbour sparse representation | as.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 computations | can.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 GMM | coef.Gmsar deviance.Gmsar fitted.Gmsar GMargminImage GMerrorsar Hausman.test.Gmsar print.Gmsar print.summary.Gmsar residuals.Gmsar summary.Gmsar |
Spatial weights matrix eigenvalues | eigenw griffith_sone subgraph_eigenw |
Spatial simultaneous autoregressive SAC model estimation by GMM | gstsls impacts.Gmsar |
Impacts in spatial lag models | HPDinterval.LagImpact impacts intImpacts plot.LagImpact print.LagImpact print.summary.LagImpact summary.LagImpact |
Compute SAR generating operator | invIrM invIrW |
Matrix exponential spatial lag model | coef.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 weights | lextrB lextrS lextrW l_max |
Spatial Durbin linear (SLX, spatially lagged X) model | create_WX impacts.SlX lmSLX predict.SlX print.SlX print.summary.SlX print.summary.WXimpact print.WXimpact summary.SlX summary.WXimpact |
Likelihood ratio test | anova.Sarlm bptest.Sarlm Hausman.test Hausman.test.Sarlm impacts.Sarlm logLik.Sarlm LR.Sarlm LR1.Sarlm Wald1.Sarlm |
MCMC sample from fitted spatial regression | MCMCsamp MCMCsamp.Sarlm MCMCsamp.Spautolm |
Moran eigenvector GLM filtering | fitted.Me_res ME print.Me_res |
Spatial simultaneous autoregressive model estimation by maximum likelihood | coef.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 objects | as.data.frame.Sarlm.pred predict.Sarlm print.Sarlm.pred |
Options for parallel support | get.ClusterOption get.coresOption get.mcOption set.ClusterOption set.coresOption set.mcOption |
Control checking of spatial object IDs | get.VerboseOption get.ZeroPolicyOption set.VerboseOption set.ZeroPolicyOption |
Create symmetric similar weights lists | similar.listw |
Semi-parametric spatial filtering | fitted.SfResult print.SfResult SpatialFiltering |
Spatial conditional and simultaneous autoregression model estimation | coef.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 estimation | impacts.MCMC_sac_G impacts.MCMC_sar_G impacts.MCMC_sem_G spBreg_err spBreg_lag spBreg_sac |
Generalized spatial two stage least squares | coef.Stsls deviance.Stsls impacts.Stsls print.Stsls print.summary.Stsls residuals.Stsls stsls summary.Stsls |
Spatial weights matrix powers traces | mom_calc mom_calc_int2 trW |