irts-methods | R Documentation |
Methods for irregular time-series objects.
## S3 method for class 'irts'
lines(x, type = "l", ...)
## S3 method for class 'irts'
plot(x, type = "l", plot.type = c("multiple", "single"),
xlab = "Time", ylab = NULL, main = NULL, ylim = NULL,
oma = c(6, 0, 5, 0), ...)
## S3 method for class 'irts'
points(x, type = "p", ...)
## S3 method for class 'irts'
print(x, format = "%Y-%m-%d %H:%M:%S", tz = "GMT",
usetz = TRUE, format.value = NULL, ...)
## S3 method for class 'irts'
time(x, ...)
## S3 method for class 'irts'
value(x, ...)
## S3 method for class 'irts'
x[i, j, ...]
x |
an object of class |
type , plot.type , xlab , ylab , main , ylim , oma |
graphical
arguments, see |
format , tz , usetz |
formatting related arguments, see
|
format.value |
a string which specifies the formatting of the
values when printing an irregular time-series
object. |
i , j |
indices specifying the parts to extract from an irregular time-series object. |
... |
further arguments passed to or from other methods: for
|
plot
is the method for plotting irregular time-series objects.
points
and lines
are the methods for drawing a sequence
of points as given by an irregular time-series object and joining the
corresponding points with line segments, respectively.
print
is the method for printing irregular time-series objects.
time
and value
are the methods for extracting the
sequence of times and the sequence of values of an irregular
time-series object.
[.irts
is the method for extracting parts of irregular
time-series objects.
For time
an object of class "POSIXct"
representing the
sequence of times. For value
a vector or matrix representing
the sequence of values.
For [.irts
an object of class "irts"
representing the
extracted part.
For plot
, points
, lines
, and print
the
irregular time-series object.
A. Trapletti
irts
,
irts-functions
n <- 10
t <- cumsum(rexp(n, rate = 0.1))
v <- rnorm(n)
x <- irts(t, v)
x
time(x)
value(x)
plot(x)
points(x)
t <- cumsum(c(t[1], rexp(n-1, rate = 0.2)))
v <- rnorm(n, sd = 0.1)
x <- irts(t, v)
lines(x, col = "red")
points(x, col = "red")
# Multivariate
t <- cumsum(rexp(n, rate = 0.1))
u <- rnorm(n)
v <- rnorm(n)
x <- irts(t, cbind(u, v))
x
x[,1]
x[1:3,]
x[1:3,1]
plot(x)
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