lm.morantest.sad {spdep}R Documentation

Saddlepoint approximation of global Moran's I test

Description

The function implements Tiefelsdorf's application of the Saddlepoint approximation to global Moran's I's reference distribution.

Usage

lm.morantest.sad(model, listw, zero.policy=FALSE, alternative="greater", 
  spChk=NULL, resfun=weighted.residuals, tol=.Machine$double.eps^0.5, maxiter=1000, tol.bounds=0.0001)
print.moransad(x, ...)
summary.moransad(object, ...)
print.summary.moransad(x, ...) 

Arguments

model an object of class lm returned by lm; weights may be specified in the lm fit, but offsets should not be used
listw a listw object created for example by nb2listw
zero.policy if TRUE assign zero to the lagged value of zones without neighbours, if FALSE assign NA
alternative a character string specifying the alternative hypothesis, must be one of greater (default), less or two.sided.
spChk should the data vector names be checked against the spatial objects for identity integrity, TRUE, or FALSE, default NULL to use get.spChkOption()
resfun default: weighted.residuals; the function to be used to extract residuals from the lm object, may be residuals, weighted.residuals, rstandard, or rstudent
tol the desired accuracy (convergence tolerance) for uniroot
maxiter the maximum number of iterations for uniroot
tol.bounds offset from bounds for uniroot
x object to be printed
object object to be summarised
... arguments to be passed through

Details

The function involves finding the eigenvalues of an n by n matrix, and numerically finding the root for the Saddlepoint approximation, and should therefore only be used with care when n is large.

Value

A list of class moransad with the following components:

statistic the value of the saddlepoint approximation of the standard deviate of global Moran's I.
p.value the p-value of the test.
estimate the value of the observed global Moran's I.
alternative a character string describing the alternative hypothesis.
method a character string giving the method used.
data.name a character string giving the name(s) of the data.
internal1 Saddlepoint omega, r and u
internal2 f.root, iter and estim.prec from uniroot
df degrees of freedom
tau eigenvalues (excluding zero values)

Author(s)

Roger Bivand Roger.Bivand@nhh.no

References

Tiefelsdorf, M. 2002 The Saddlepoint approximation of Moran's I and local Moran's Ii reference distributions and their numerical evaluation. Geographical Analysis, forthcoming; see also Tiefelsdorf's SPSS code: http://geog-www.sbs.ohio-state.edu/faculty/tiefelsdorf/GeoStat.htm.

See Also

lm.morantest

Examples

data(eire)
e.lm <- lm(OWNCONS ~ ROADACC, data=eire.df)
lm.morantest(e.lm, nb2listw(eire.nb))
lm.morantest.sad(e.lm, nb2listw(eire.nb))
summary(lm.morantest.sad(e.lm, nb2listw(eire.nb)))
e.wlm <- lm(OWNCONS ~ ROADACC, data=eire.df, weights=RETSALE)
lm.morantest(e.wlm, nb2listw(eire.nb), resfun=rstudent)
lm.morantest.sad(e.wlm, nb2listw(eire.nb), resfun=rstudent)

[Package spdep version 0.3-12 Index]