EBest {spdep} | R Documentation |
The function computes global empirical Bayes estimates for rates "shrunk" to the overall mean.
EBest(n, x)
n |
a numeric vector of counts of cases |
x |
a numeric vector of populations at risk |
Details of the implementation are to be found in Marshall, p. 284–5, and Bailey and Gatrell p. 303–306 and exercise 8.2, pp. 328–330.
A data frame with two columns:
raw |
a numerical vector of raw (crude) rates |
estmm |
a numerical vector of empirical Bayes estimates |
a |
global method of moments phi value |
m |
global method of moments gamma value |
Roger Bivand Roger.Bivand@nhh.no
Marshall R M (1991) Mapping disease and mortality rates using Empirical Bayes Estimators, Applied Statistics, 40, 283–294; Bailey T, Gatrell A (1995) Interactive Spatial Data Analysis, Harlow: Longman, pp. 303–306.
data(auckland) res <- EBest(auckland$Deaths.1977.85, 9*auckland$Under.5.1981) attr(res, "parameters") cols <- grey(6:2/7) brks <- c(-Inf,2,2.5,3,3.5,Inf) library(maptools) plot(auckpolys, col=cols[findInterval(res$estmm*1000, brks)], forcefill=FALSE) legend(c(70,90), c(70,95), fill=cols, legend=leglabs(brks), bty="n") title(main="Global moment estimator of infant mortality per 1000 per year")