spdep (version 0.3-8)

choynowski: Choynowski probability map values

Description

Calculates Choynowski probability map values.

Usage

choynowski(n, x, row.names=NULL, tol = .Machine$double.eps^0.5)

Arguments

n

a numeric vector of counts of cases

x

a numeric vector of populations at risk

row.names

row names passed through to output data frame

tol

accumulate values for observed counts >= expected until value less than tol

Value

• A data frame with columns:
• pmap
  Poisson probability map values: probablility of getting a more ``extreme'' count than actually observed, one-tailed with less than expected and more than expected folded together
• type
  logical: TRUE if observed count less than expected

References

Choynowski, M (1959) Maps based on probabilities, Journal of the American Statistical Association, 54, 385--388; Cressie, N, Read, TRC (1985), Do sudden infant deaths come in clusters? Statistics and Decisions, Supplement Issue 2, 333--349; Bailey T, Gatrell A (1995) Interactive Spatial Data Analysis, Harlow: Longman, pp. 300--303.

See Also

probmap

Examples

data(auckland)
res <- choynowski(auckland$Deaths.1977.85, 9*auckland$Under.5.1981)
res1 <- probmap(auckland$Deaths.1977.85, 9*auckland$Under.5.1981)
table(abs(res$pmap - res1$pmap) < 0.00001, res$type)
plot(auckpolys, forcefill=FALSE)
lt005 <- (res$pmap < 0.05) & (res$type)
ge005 <- (res$pmap < 0.05) & (!res$type)
plot(subset(auckpolys, lt005), add=TRUE, col=grey(2/7), forcefill=FALSE) 
plot(subset(auckpolys, ge005), add=TRUE, col=grey(5/7), forcefill=FALSE)
legend(c(70,90), c(70,95), fill=grey(c(2,5)/7),
 legend=c("low", "high"), bty="n")