Function reference • spdep

All functions
`oldcol`	Columbus OH spatial analysis data set - old numbering
`EBImoran.mc()`	Permutation test for empirical Bayes index
`EBest()`	Global Empirical Bayes estimator
`EBlocal()`	Local Empirical Bayes estimator
`LOSH()`	Local spatial heteroscedasticity
`LOSH.cs()`	Chi-square based test for local spatial heteroscedasticity
`LOSH.mc()`	Bootstrapping-based test for local spatial heteroscedasticity
`SD.RStests()`	Rao's score and adjusted Rao's score tests of linear hypotheses for spatial Durbin and spatial Durbin error models
`aggregate(<nb>)`	Aggregate a spatial neighbours object
`airdist()`	Measure distance from plot
`autocov_dist()`	Distance-weighted autocovariate
`bhicv`	Data set with 4 life condition indices of Belo Horizonte region
`card()`	Cardinalities for neighbours lists
`cell2nb()` `vi2mrc()`	Generate neighbours list for grid cells
`choynowski()`	Choynowski probability map values
`columbus`	Columbus OH spatial analysis data set
`n.comp.nb()`	Depth First Search on Neighbor Lists
`diffnb()`	Differences between neighbours lists
`dnearneigh()`	Neighbourhood contiguity by distance
`droplinks()`	Drop links in a neighbours list
`edit(<nb>)`	Interactive editing of neighbours lists
`eire`	Eire data sets
`geary()`	Compute Geary's C
`geary.mc()`	Permutation test for Geary's C statistic
`geary.test()`	Geary's C test for spatial autocorrelation
`globalG.test()`	Global G test for spatial autocorrelation
`gabrielneigh()` `relativeneigh()` `soi.graph()` `graph2nb()` `plot(<Gabriel>)` `plot(<relative>)`	Graph based spatial weights
`grid2nb()`	Construct neighbours for a GridTopology
`hotspot()`	Cluster classifications for local indicators of spatial association
`include.self()` `remove.self()`	Include self in neighbours list
`joincount.mc()`	Permutation test for same colour join count statistics
`joincount.multi()` `print(<jcmulti>)`	BB, BW and Jtot join count statistic for k-coloured factors
`joincount.test()` `print(<jclist>)`	BB join count statistic for k-coloured factors
`knearneigh()`	K nearest neighbours for spatial weights
`knn2nb()`	Neighbours list from knn object
`lag(<listw>)`	Spatial lag of a numeric vector
`lee()`	Compute Lee's statistic
`lee.mc()`	Permutation test for Lee's L statistic
`lee.test()`	Lee's L test for spatial autocorrelation
`listw2sn()` `sn2listw()`	Spatial neighbour sparse representation
`lm.RStests()` `lm.LMtests()` `print(<RStestlist>)` `summary(<RStestlist>)` `print(<RStestlist.summary>)`	Rao's score (a.k.a Lagrange Multiplier) diagnostics for spatial dependence in linear models
`lm.morantest()`	Moran's I test for residual spatial autocorrelation
`lm.morantest.exact()` `print(<moranex>)`	Exact global Moran's I test
`lm.morantest.sad()` `print(<moransad>)` `summary(<moransad>)` `print(<summary.moransad>)`	Saddlepoint approximation of global Moran's I test
`localC()` `localC_perm()`	Compute Local Geary statistic
`localG()` `localG_perm()`	G and Gstar local spatial statistics
`localGS()`	A local hotspot statistic for analysing multiscale datasets
`local_joincount_bv()`	Calculate the local bivariate join count
`local_joincount_uni()`	Calculate the local univariate join count
`localmoran()` `localmoran_perm()`	Local Moran's I statistic
`localmoran.exact()` `localmoran.exact.alt()` `print(<localmoranex>)` `as.data.frame(<localmoranex>)`	Exact local Moran's Ii tests
`localmoran.sad()` `print(<localmoransad>)` `summary(<localmoransad>)` `print(<summary.localmoransad>)` `listw2star()`	Saddlepoint approximation of local Moran's Ii tests
`localmoran_bv()`	Compute the Local Bivariate Moran's I Statistic
`mat2listw()`	Convert a square spatial weights matrix to a weights list object
`moran()`	Compute Moran's I
`moran.mc()`	Permutation test for Moran's I statistic
`moran.plot()`	Moran scatterplot
`moran.test()`	Moran's I test for spatial autocorrelation
`moran_bv()`	Compute the Global Bivariate Moran's I
`mstree()`	Find the minimal spanning tree
`nb2INLA()`	Output spatial neighbours for INLA
`nb2WB()` `listw2WB()`	Output spatial weights for WinBUGS
`nb2blocknb()`	Block up neighbour list for location-less observations
`nb2lines()` `listw2lines()` `df2sn()`	Use vector files for import and export of weights
`nb2listw()` `listw2U()`	Spatial weights for neighbours lists
`nb2listwdist()`	Distance-based spatial weights for neighbours lists
`nb2mat()` `listw2mat()`	Spatial weights matrices for neighbours lists
`nbcost()` `nbcosts()`	Compute cost of edges
`nbdists()`	Spatial link distance measures
`nblag()` `nblag_cumul()`	Higher order neighbours lists
`intersect.nb()` `union.nb()` `setdiff.nb()` `complement.nb()`	Set operations on neighborhood objects
`p.adjustSP()`	Adjust local association measures' p-values
`plot(<mst>)`	Plot the Minimum Spanning Tree
`plot(<nb>)` `plot(<listw>)`	Plot a neighbours list
`plot(<skater>)`	Plot the object of skater class
`poly2nb()`	Construct neighbours list from polygon list
`probmap()`	Probability mapping for rates
`prunecost()`	Compute cost of prune each edge
`prunemst()`	Prune a Minimun Spanning Tree
`read.gal()` `read.geoda()`	Read a GAL lattice file into a neighbours list
`read.gwt2nb()` `write.sn2gwt()` `read.dat2listw()` `write.sn2dat()`	Read and write spatial neighbour files
`Rotation()`	Rotate a set of point by a certain angle
`set.mcOption()` `get.mcOption()` `set.coresOption()` `get.coresOption()` `set.ClusterOption()` `get.ClusterOption()`	Options for parallel support
`set.spChkOption()` `get.spChkOption()` `chkIDs()` `spNamedVec()` `set.VerboseOption()` `get.VerboseOption()` `set.ZeroPolicyOption()` `get.ZeroPolicyOption()` `set.SubgraphOption()` `get.SubgraphOption()` `set.listw_is_CsparseMatrix_Option()` `get.listw_is_CsparseMatrix_Option()`	Control checking of spatial object IDs
`skater()`	Spatial 'K'luster Analysis by Tree Edge Removal
`sp.correlogram()` `plot(<spcor>)` `print(<spcor>)`	Spatial correlogram
`sp.mantel.mc()` `plot(<mc.sim>)`	Mantel-Hubert spatial general cross product statistic
`aple.plot()` `localAple()` `aple.mc()` `aple()` `lextrB()` `lextrW()` `lextrS()` `griffith_sone()` `subgraph_eigenw()` `mom_calc()` `mom_calc_int2()` `stsls()` `impacts(<stsls>)` `GMerrorsar()` `summary(<gmsar>)` `gstsls()` `impacts(<gmsar>)` `Hausman.test(<gmsar>)` `lagmess()` `ME()` `SpatialFiltering()` `LR.sarlm()` `logLik(<sarlm>)` `LR1.sarlm()` `Wald1.sarlm()` `Hausman.test(<sarlm>)` `as.spam.listw()` `as_dgRMatrix_listw()` `as_dsTMatrix_listw()` `as_dsCMatrix_I()` `as_dsCMatrix_IrW()` `Jacobian_W()` `powerWeights()` `plot(<lagImpact>)` `print(<lagImpact>)` `summary(<lagImpact>)` `HPDinterval(<lagImpact>)` `intImpacts()` `can.be.simmed()` `eigenw()` `similar.listw()` `do_ldet()` `jacobianSetup()` `cheb_setup()` `mcdet_setup()` `eigen_setup()` `eigen_pre_setup()` `spam_setup()` `spam_update_setup()` `Matrix_setup()` `Matrix_J_setup()` `LU_setup()` `LU_prepermutate_setup()` `moments_setup()` `SE_classic_setup()` `SE_whichMin_setup()` `SE_interp_setup()` `MCMCsamp()` `spautolm()` `summary(<spautolm>)` `spBreg_sac()` `impacts(<MCMC_sar_g>)` `impacts(<MCMC_sem_g>)` `impacts(<MCMC_sac_g>)` `spBreg_err()` `spBreg_lag()` `predict(<SLX>)` `lmSLX()` `impacts(<SLX>)` `create_WX()` `anova(<sarlm>)` `bptest.sarlm()` `errorsarlm()` `impacts(<sarlm>)` `lagsarlm()` `predict(<sarlm>)` `print(<sarlm.pred>)` `as.data.frame(<sarlm.pred>)` `residuals(<sarlm>)` `deviance(<sarlm>)` `coef(<sarlm>)` `vcov(<sarlm>)` `fitted(<sarlm>)` `sacsarlm()` `summary(<sarlm>)` `print(<sarlm>)` `print(<summary.sarlm>)` `trW()`	Defunct Functions in Package spdep
`spdep()`	Return package version number
`spweights.constants()` `Szero()`	Provides constants for spatial weights matrices
`ssw()`	Compute the sum of dissimilarity
`subset(<listw>)`	Subset a spatial weights list
`subset(<nb>)`	Subset a neighbours list
`summary(<nb>)` `print(<nb>)` `summary(<listw>)` `print(<listw>)`	Print and summary function for neighbours and weights lists
`is.symmetric.nb()` `sym.attr.nb()` `make.sym.nb()` `old.make.sym.nb()` `is.symmetric.glist()`	Test a neighbours list for symmetry
`tolerance.nb()`	Function to construct edges based on a tolerance angle and a maximum distance
`tri2nb()`	Neighbours list from tri object
`write.nb.gal()`	Write a neighbours list as a GAL lattice file

Reference

All functions