showClass("sts")
## create an sts object from time-series data
salmonellaDF <- read.table(system.file("extdata/salmonella.agona.txt",
package = "surveillance"), header = TRUE)
str(salmonellaDF)
salmonella <- with(salmonellaDF,
sts(observed = observed, state = state,
start = c(1990, 1), frequency = 52))
salmonella
plot(salmonella)
## these data are also available as a legacy "disProg" object in the package
data(salmonella.agona)
stopifnot(all.equal(salmonella, disProg2sts(salmonella.agona)))
## A typical dataset with weekly counts of measles from several districts
data("measlesWeserEms")
measlesWeserEms
## reconstruct data("measlesWeserEms") from its components
counts <- observed(measlesWeserEms)
map <- measlesWeserEms@map
populationFrac <- population(measlesWeserEms)
weserems_nbOrder <- neighbourhood(measlesWeserEms)
## orders of adjacency can also be determined from the map
if (requireNamespace("spdep")) {
stopifnot(identical(weserems_nbOrder,
nbOrder(poly2adjmat(map))))
}
mymeasles <- sts(counts, start = c(2001, 1), frequency = 52,
population = populationFrac,
neighbourhood = weserems_nbOrder, map = map)
stopifnot(identical(mymeasles, measlesWeserEms))
## convert ts/mts object to sts
z <- ts(matrix(rpois(300,10), 100, 3), start = c(1961, 1), frequency = 12)
z.sts <- as(z, "sts")
plot(z.sts)
## conversion of "sts" objects to the quasi-standard "xts" class
if (requireNamespace("xts")) {
z.xts <- as.xts.sts(z.sts)
plot(z.xts)
}
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