| sts-class {surveillance} | R Documentation |
This is a rather leightweight class to implement multivariate time series of count 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.
week:numeric specifying the week
numbers. Actually this is not really used at the moment. freq:freq corresponds to 52, in case of monthly data freq is 12.start:observed:length(week) times the
number of regions containing the weekly/monthly number of counts in
each region. The colnames of the matrix should match the ID values of
the shapes in the map slot.state:observed containing booleans whether at the specific time point there was an outbreak in the regionalarm:observed specifying whether an outbreak detection algorithm declared a specific time point in the region as having an alarm. If the object containins just observations then this slot is null. upperbound:neighbourhood:populationFrac:matrix.map:SpatialPolygonsDataFrame providing a shape of the areas which are monitored. control:list, thais is a rather free data type to be returned by the surveillance algorithms. signature(x = "sts"):
extract number of rows of the observed matrix slot. The
dimension of the other matrix slots is similar.signature(x = "sts"):
extract number of columns of the observed matrix slot.signature(x = "sts"): extract matrix dimensions of
observed using dim.signature(x="sts",do.NULL="missing",prefix="missing"):
extract colnames of the observed matrix.signature(x="sts"): the internal function
init.sts is called, which assigns all slots. signature(x="sts"): see
aggregate,sts-method
signature(x="sts",y="missing",function(x, y, type,...)...): this function is
the successor of the plot.disProg and
plot.survRes functions. It takes (more or less) the
same arguments as plot.survRes. The most important
difference is the type of plot, which is specified using
type. See show,sts-method for details.
M. Höhle
data("ha")
shp <- system.file("shapes/berlin.shp",package="surveillance")
ha <- disProg2sts(ha, map=readShapePoly(shp,IDvar="SNAME"))
plot(ha,type=observed ~ 1 | unit)