sts_ggplot: Time-Series Plots for '"sts"' Objects Using 'ggplot2'

In surveillance: Temporal and Spatio-Temporal Modeling and Monitoring of Epidemic Phenomena

Time-Series Plots for "sts" Objects Using ggplot2

Description

A simple ggplot2 variant of stsplot_time, based on a “tidy” version of the "sts" object via tidy.sts. It uses a date axis and thus only works for time series indexed by dates or with a standard frequency (daily, (bi-)weekly, or monthly).

Usage

autoplot.sts(object, population = FALSE, units = NULL,
             as.one = FALSE, scales = "fixed", width = NULL, ...)

Arguments

object	an object of class "sts".
population	logical indicating whether observed(object) should be divided by population(object). The population argument can also be a scalar, which is used to scale the denominator population(object), i.e., observed(object) is divided by population(object) / population. For instance, if population(object) contains raw population numbers, population = 1000 could be used to plot the incidence per 1000 inhabitants.
units	optional integer or character vector to select the units (=columns of object) to plot. The default (NULL) is to plot all time series.
as.one	logical indicating if all time series should be plotted in one panel with geom_line. By default, the time series are plotted in separate panels (using geom_col).
scales	passed to facet_wrap (for as.one=FALSE). By default, all panels use a common ylim (and xlim).
width	bar width, passed to geom_col. Defaults to 7 for weekly time series.
...	unused (argument of the generic).

Value

a "ggplot" object.

Author(s)

Sebastian Meyer

See Also

stsplot_time for the traditional plots.

Examples

## compare traditional plot() with ggplot2-based autoplot.sts()
if (requireNamespace("ggplot2")) {
    data("measlesDE")
    plot(measlesDE, units = 1:2)
    autoplot.sts(measlesDE, units = 1:2)
}

## weekly incidence: population(measlesDE) gives population fractions,
## which we need to multiply by the total population
if (require("ggplot2", quietly = TRUE)) {
    autoplot.sts(measlesDE, population = 1000000/82314906) +
        ylab("Weekly incidence [per 1'000'000 inhabitants]")
}

surveillance documentation built on Nov. 4, 2024, 3 a.m.