A method for printing objects of class egf.
# S3 method for egf
plot(x, type = c("interval", "cumulative", "rt"),
time_as = c("Date", "numeric"), delta = 1, log = TRUE, zero = NA,
show_predict = TRUE, show_doubling = FALSE, level = 0.95,
control = egf_control_plot(), cache = NULL, plot = TRUE,
subset = NULL, order = NULL, xlim = NULL, ylim = NULL,
main = NULL, sub = NULL, xlab = NULL, ylab = NULL, ...)A data frame inheriting from class plot.egf.
If argument cache was supplied in the function call,
then this data frame is the result of augmenting cache
with any new computations.
an egf object.
a character string indicating a type of plot. The options are:
interval incidence ("interval"),
cumulative incidence ("cumulative"), and
per capita growth rate ("rt").
a character string indicating how numeric times are displayed
on the bottom axis. The options are:
as is ("numeric") and
with a calendar ("Date").
In the latter case, horizontal user coordinates on measure time
in days since midnight on January 1, 1970.
a positive number indicating a step size on the time axis.
Predicted curves are evaluated on a grid with this spacing.
When type = "interval", counts observed over shorter
or longer intervals delta0 are scaled by a factor
of delta/delta0 so that their scale matches that of
predicted incidence. Scaled counts can be highlighted via
control. If x specifies a model with day of
week effects, then delta = 1 is used unconditionally.
a logical. If TRUE, then the dependent variable is plotted
on a logarithmic scale.
a positive number indicating a line on which to plot zeros when
log = TRUE and type = "interval" or "cumulative".
NA is to place zeros on the bottom axis.
NULL is to suppress zeros.
an integer flag: 2 is to draw predicted curves with confidence bands, 1 is draw predicted curves only, 0 is to draw neither.
an integer flag: 2 is to print initial doubling time estimates in the top margin with confidence intervals, 1 is to print estimates only, 0 is to print neither. Nothing is printed for models without a well-defined initial exponential growth rate.
a number in the interval \((0,1)\) indicating confidence level,
used when show_predict = 2 or show_doubling = 2.
an egf_control_plot object controlling the
appearance of most plot elements.
a plot.egf object returned by a previous evaluation of
plot(x, ...). Fitted and predicted values and standard
errors stored in cache are reused to avoid recomputation.
a logical. If FALSE, then plotting does not occur.
Useful when only the returned plot.egf object is desired.
an index vector for the rows of
mf = model.frame(object, "combined") or a language object
evaluating to such a vector.
Only time series corresponding to indexed rows are plotted and
only fitting windows corresponding to indexed rows are highlighted;
the default is to plot all series and to highlight all windows.
Evaluation of language objects follows the implementation of
subset.data.frame.
a permutation of seq_len(nrow(mf)) or a language object
evaluating in mf to such a vector.
order indicates the order in which time series are plotted;
the default indicates the original order.
numeric vectors of length 2 specifying axis limits, which are
recycled for all plots.
If time_as = "Date", then xlim can instead be a
Date, POSIXct, or POSIXlt
vector.
character or expression vectors or (main, sub)
language objects evaluating in mf to such vectors.
These are used to generate plot (main, sub) and
axis (xlab, ylab) labels.
unused optional arguments.
Computation of fitted and predicted values and standard errors is performed before any plots are created. To avoid waste of computation time, cached computations are returned even if an error is thrown during plotting. To ensure that the cache is preserved, assign the result of the function call to a name:
cache <- plot(x, \dots).
Caching functionality must be used with care, as mismatch between
x and cache will not be detected. Constructions such
as plot(y, cache = plot(x, ...), ...), where x
and y are different egf objects, should not be expected
to produce correct results.
The generic function plot.
example("egf", package = "epigrowthfit")
l <- list(legend = list(cex = 0.8),
value = list(cex = 0.8, font = 2),
ci = list(cex = 0.8))
control <- egf_control_plot(doubling = l)
op <- par(mar = c(3.5, 5, 5, 1))
plot(m1,
type = "interval",
show_predict = 2L,
show_doubling = 2L,
control = control)
plot(m1,
type = "cumulative",
main = "Fitted exponential model",
sub = quote(paste("Country", country)))
par(op)
op <- par(mar = c(3.5, 9.5, 5, 1))
plot(m1, type = "rt", subset = quote(country %in% LETTERS[4:6]))
par(op)
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