lm.morantest.sad {spdep} | R Documentation |
The function implements Tiefelsdorf's application of the Saddlepoint approximation to global Moran's I's reference distribution.
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, ...)
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 |
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.
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) |
Roger Bivand Roger.Bivand@nhh.no
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.
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)