Locations of cases of Burkitt's lymphoma in the Western Nile district of Uganda 1960-1975. The time variable is recorded as the number of days starting from an origin of 1 Jan 1960. The examples given below show how the chron() function and derived time structures may be used to analyse the data in the time dimension.

data(burkitt)

Format

The data is provided as a data table:

xnumericgrid eastings
ynumericgrid northings
tnumericday number starting at 1/1/1960 of onset
agenumericage of child patient
datesfactorday as string yy-mm-dd

as a points object burpts of burkitt$x and burkitt$y; and a point object of the area boundary burbdy.

Source

Williams, E. H. et al. 1978, - Bailey and Gatrell 1995, ch. 3.

References

Bailey, T. C. and Gatrell, A. C. 1995, Interactive spatial data analysis. Longman, Harlow.

Examples

data(burkitt)
burDates <- as.Date(as.character(burkitt$dates), "%y-%m-%d")
res <- aggregate(rep(1, length(burDates)), list(quarters(burDates), format(burDates, "%y")), sum)
plot(as.numeric(as.character(res$Group.2)) +
 0.25*(as.numeric(substr(as.character(res$Group.1), 2, 2))-1),
 res$x, type="h", lwd=3, col=ifelse(as.character(res$Group.1)=="Q3",
 "grey","red"), xlab="year", ylab="count", xaxt="n")
axis(1, at=seq(61,75,4), labels=format(seq.Date(as.Date("1961/1/1"),
 as.Date("1975/1/1"), "4 years")))
title("Plot of Burkitt's lymphoma in West Nile district,\nQ3 grey shaded")

op <- par(mfrow=c(3,5))
for (i in unique(format(burDates, "%y"))) {
  polymap(burbdy)
  pointmap(burpts[which(format(burDates, "%y") == i),], add=TRUE, pch=19)
  title(main=paste("19", i, sep=""))
}

par(op)
op <- par(mfrow=c(2,2))
for (i in c("Q1", "Q2", "Q3", "Q4")) {
  polymap(burbdy)
  pointmap(burpts[which(unclass(quarters(burDates)) == i),], add=TRUE,
pch=19)
  title(main=i)
}

par(op)
op <- par(mfrow=c(3,4))
for (i in months(seq(as.Date("70-01-01", "%y-%m-%d"), len=12, by="1 month"))) {
  polymap(burbdy)
  pointmap(burpts[which(unclass(months(burDates)) == i),], add=TRUE, pch=19)
  title(main=i)
}

par(op)