Methods for Irregular Time-Series Objects
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
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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