EBlocal
From spdep v0.69
by Roger Bivand
Local Empirical Bayes estimator
The function computes local empirical Bayes estimates for rates "shrunk" to a neighbourhood mean for neighbourhoods given by the nb
neighbourhood list.
 Keywords
 spatial
Usage
EBlocal(ri, ni, nb, zero.policy = NULL, spChk = NULL, geoda=FALSE)
Arguments
 ri
 a numeric vector of counts of cases the same length as the neighbours list in nb
 ni
 a numeric vector of populations at risk the same length as the neighbours list in nb
 nb
 a
nb
object of neighbour relationships  zero.policy
 default NULL, use global option value; if TRUE assign zero to the lagged value of zones without neighbours, if FALSE assign NA
 spChk
 should the data vector names be checked against the spatial objects for identity integrity, TRUE, or FALSE, default NULL to use
get.spChkOption()
 geoda
 default=FALSE, following Marshall's algorithm as interpreted by Bailey and Gatrell, pp. 305307, and exercise 8.2, pp. 328330 for the definition of phi; TRUE for the definition of phi used in GeoDa (see discussion on OpenSpace mailing list June 2003: http://agec221.agecon.uiuc.edu/pipermail/openspace/2003June/thread.html)
Details
Details of the implementation are to be found in Marshall, p. 286, and Bailey and Gatrell p. 307 and exercise 8.2, pp. 328330. The example results do not fully correspond to the sources because of slightly differing neighbourhoods, but are generally close.
Value

A data frame with two columns:and a
parameters
attribute list with components:References
Marshall R M (1991) Mapping disease and mortality rates using Empirical Bayes Estimators, Applied Statistics, 40, 283294; Bailey T, Gatrell A (1995) Interactive Spatial Data Analysis, Harlow: Longman, pp. 303306.
See Also
Examples
example(auckland)
res < EBlocal(auckland$M77_85, 9*auckland$Und5_81, auckland.nb)
brks < c(Inf,2,2.5,3,3.5,Inf)
cols < grey(6:2/7)
plot(auckland, col=cols[findInterval(res$est*1000, brks, all.inside=TRUE)])
legend("bottomleft", fill=cols, legend=leglabs(brks), bty="n")
title(main="Local moment estimator of infant mortality per 1000 per year")
Community examples
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