plot.Recur {reReg} | R Documentation |
Produce Event Plot or Mean Cumulative Function Plot
Description
Plot the event plot or the mean cumulative function (MCF) from an Recur
object.
Usage
## S3 method for class 'Recur'
plot(
x,
mcf = FALSE,
event.result = c("increasing", "decreasing", "asis"),
event.calendarTime = FALSE,
mcf.adjustRiskset = TRUE,
mcf.conf.int = FALSE,
control = list(),
...
)
Arguments
x |
an object of class |
mcf |
an optional logical value indicating whether the mean cumulative function (MCF) will
be plotted instead of the event plot. When |
event.result |
an optional character string that is passed to the
|
event.calendarTime |
an optional logical value indicating whether to plot in calendar time.
When |
mcf.adjustRiskset |
an optional logical value that is passed to
the |
mcf.conf.int |
an optional logical value that is passed to
the |
control |
a list of control parameters. See Details. |
... |
additional graphical parameters to be passed to methods. |
Details
The argument control
consists of options with argument defaults to a list with
the following values:
- xlab
customizable x-label, default value is "Time".
- ylab
customizable y-label, default value is "Subject" for event plot and "Cumulative mean" for MCF plot.
- main
customizable title, the default value is "Recurrent event plot" when
mcf = FALSE
and "Sample cumulative mean function plot" whenmcf = TRUE
.- terminal.name
customizable label for terminal event, the default value is "Terminal event".
- recurrent.name
customizable legend title for recurrent event, the default value is "Recurrent events".
- recurrent.types
customizable label for recurrent event type, the default value is
NULL
.- alpha
between 0 and 1, controls the transparency of points.
The xlab
, ylab
and main
parameters can be specified
outside of the control
list.
Value
A ggplot
object.
References
Nelson, W. B. (1995) Confidence Limits for Recurrence Data-Applied to Cost or Number of Product Repairs. Technometrics, 37(2): 147–157.
See Also
Examples
data(simDat)
reObj <- with(simDat, Recur(t.start %to% t.stop, id, event, status))
## Event plots:
plot(reObj)
plot(reObj, event.result = "decreasing")
## With (hypothetical) multiple event types
simDat$event2 <- with(simDat, ifelse(t.stop > 10 & event > 0, 2, event))
reObj2 <- with(simDat, Recur(t.start %to% t.stop, id, event2, status))
plot(reObj2)
## With (hypothetical) calendar times
simDat2 <- simDat
simDat2$t.start <- as.Date(simDat2$t.start + simDat2$x2 * 5, origin = "20-01-01")
simDat2$t.stop <- as.Date(simDat2$t.stop + simDat2$x2 * 5, origin = "20-01-01")
reObj3 <- with(simDat2, Recur(t.start %to% t.stop, id, event, status))
plot(reObj3, event.calendarTime = TRUE)
## MCF plots
plot(reObj, mcf = TRUE)
plot(reObj, mcf = TRUE, mcf.adjustRiskset = FALSE)
library(reReg)
data(simDat)
reObj <- with(simDat, Recur(t.start %to% t.stop, id, event, status))
summary(reObj)