irtsmethods  R Documentation 
Methods for irregular timeseries 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 timeseries
object. 
i, j 
indices specifying the parts to extract from an irregular timeseries object. 
... 
further arguments passed to or from other methods: for

plot
is the method for plotting irregular timeseries objects.
points
and lines
are the methods for drawing a sequence
of points as given by an irregular timeseries object and joining the
corresponding points with line segments, respectively.
print
is the method for printing irregular timeseries objects.
time
and value
are the methods for extracting the
sequence of times and the sequence of values of an irregular
timeseries object.
[.irts
is the method for extracting parts of irregular
timeseries 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 timeseries object.
A. Trapletti
irts
,
irtsfunctions
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(n1, 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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