EBest {spdep}R Documentation

Global Empirical Bayes estimator

Description

The function computes global empirical Bayes estimates for rates "shrunk" to the overall mean.

Usage

EBest(n, x)

Arguments

n a numeric vector of counts of cases
x a numeric vector of populations at risk

Details

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.

Value

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

Author(s)

Roger Bivand Roger.Bivand@nhh.no

References

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.

See Also

EBlocal, probmap, EBImoran.mc

Examples

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")

[Package spdep version 0.3-12 Index]