surveillance (version 1.11.0)

sts-class: Class "sts" -- surveillance time series

Description

This is a lightweight S4 class to implement multivariate time series of counts used for public health surveillance data. The class captures the time series data as well as the spatial layout of the regions, where the data originate from.

encoding

latin1

Examples

if (requireNamespace("maptools")) {
    # load disProg-object "ha" and convert to S4-class "sts"
    data("ha")
    shpfile <- system.file("shapes/berlin.shp",package="surveillance")
    ha.sts <- disProg2sts(ha, map=maptools::readShapePoly(shpfile,IDvar="SNAME"))
} else {
    data("ha.sts")
    # is almost identical to the above except that German umlauts
    # have been replaced in 'ha.sts@map@data$BEZIRK' for compatibility reasons
}

ha.sts
plot(ha.sts, type = observed ~ 1 | unit)

## 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 to the quasi-standard "xts" class is also possible
## -> enables interactive time series plots using package "dygraphs"
if (require("xts")) {
    z.xts <- as.xts(z.sts)
    plot(z.xts)
}

## reconstruct 'measlesWeserEms' from its components
data("measlesWeserEms")
measlesWeserEms
counts <- observed(measlesWeserEms)
map <- measlesWeserEms@map
populationFrac <- measlesWeserEms@populationFrac
weserems_nbOrder <- if(requireNamespace("spdep")) {
    # determine adjacency orders from the map
    nbOrder(poly2adjmat(map), maxlag = 10)
} else {
    # use the stored neighbourhood structure
    neighbourhood(measlesWeserEms)
}
mymeasles <- sts(observed = counts, start = c(2001, 1), frequency = 52,
    neighbourhood = weserems_nbOrder, map = map, population = populationFrac)
stopifnot(identical(mymeasles, measlesWeserEms))