sp.correlogram {spdep}R Documentation

Spatial correlogram

Description

Spatial correlograms for Moran's I and the autocorrelation coefficient, with print and plot helper functions.

Usage

sp.correlogram(neighbours, var, order = 1, method = "corr", style = "W", 
  randomisation = TRUE, zero.policy = FALSE, spChk=NULL)
plot.spcor(x, main, ylab, ylim, ...)
print.spcor(x, ...)

Arguments

neighbours an object of class nb
var a numeric vector
order maximum lag order
method "corr" for correlation, "I" for Moran's I
style style can take values W, B, C, and S
randomisation variance of I calculated under the assumption of randomisation, if FALSE normality
zero.policy If FALSE stop with error for any empty neighbour sets, if TRUE permit the weights list to be formed with zero-length weights vectors
spChk should the data vector names be checked against the spatial objects for identity integrity, TRUE, or FALSE, default NULL to use get.spChkOption()
x an object from sp.correlogram() of class spcor
main an overall title for the plot
ylab a title for the y axis
ylim the y limits of the plot
... further arguments passed through

Value

returns a list of class spcor:

res for "corr" a vector of values; for "I", a matrix of estimates of "I", expectations, and variances
method "I" or "corr"
cardnos list of tables of neighbour cardinalities for the lag orders used
var variable name

Author(s)

Roger Bivand, Roger.Bivand@nhh.no

References

Cliff, A. D., Ord, J. K. 1981 Spatial processes, Pion, pp. 118–122, Martin, R. L., Oeppen, J. E. 1975 The identification of regional forecasting models using space-time correlation functions, Transactions of the Institute of British Geographers, 66, 95–118.

See Also

nblag, moran

Examples

data(nc.sids)
ft.SID74 <- sqrt(1000)*(sqrt(nc.sids$SID74/nc.sids$BIR74) +
  sqrt((nc.sids$SID74+1)/nc.sids$BIR74))
tr.SIDS74 <- ft.SID74*sqrt(nc.sids$BIR74)
names(tr.SIDS74) <- rownames(nc.sids)
print(sp.correlogram(ncCC89.nb, tr.SIDS74, order=8, method="corr",
 zero.policy=TRUE))
print(sp.correlogram(ncCC89.nb, tr.SIDS74, order=8, method="I",
 zero.policy=TRUE))
plot(sp.correlogram(ncCC89.nb, tr.SIDS74, order=8, method="I",
 zero.policy=TRUE))
plot(sp.correlogram(ncCC89.nb, tr.SIDS74, order=8, method="corr",
 zero.policy=TRUE))
drop.no.neighs <- !(1:length(ncCC89.nb) %in% which(card(ncCC89.nb) == 0))
sub.ncCC89.nb <- subset(ncCC89.nb, drop.no.neighs)
plot(sp.correlogram(sub.ncCC89.nb, subset(tr.SIDS74,  drop.no.neighs),
 order=8, method="corr"))

[Package spdep version 0.3-12 Index]