ts(data = NA, start = 1, end = numeric(0), frequency = 1, deltat = 1, ts.eps = .Options$ts.eps) as.ts(x) is.ts(x) print(ts.obj, calendar, ...) plot(ts.obj, ...)
data
| a vector or matrix the observed time-series values. |
start
| the time of the first observation. |
end
| the time of the last observation. |
frequency
| the number of observations per unit of time. |
deltat
|
the fraction of the sampling period between successive
observations; e.g., 1/12 for monthly data.
Only one of frequency or deltat should be provided.
|
ts.eps
|
time series comparison tolerance. Frequencies are
considered equal if their absolute difference is less than
ts.eps.
|
ts is used to create time-series objects. These
are vector or matrices with class of "ts" (and additional
attributes) which represent data which has been sampled at equispaced
points in time. In the matrix case, each column of the matrix
data is assumed to contain a single (univariate) time series.
The value of argument frequency is used when the series is
sampled an interal number of times in each unit time interval. For
example, one could use a value of 7 for frequency when
the data are sampled daily, and the natural time period is a week, or
12 when the data are sampled monthly and the natural time
period is a year.
start and end can either be integers which correspond to
natural time units, or vectors of two integers, which give a natural
time unit and a (1-based) number of samples into the time unit.
as.ts and is.ts respectively coerce a vector into a
time-series and test whether an object is a time series.
Time series have methods associated with the generic print and
plot functions. The argument calendar to the print
method can be used to enable/disable the display of information about
month names, quarter names or year when printing.
frequency,
start,
end,
time,
window.
ts(1:10, frequency = 4, start = c(1959, 2)) # 2nd Quarter of 1959
print( ts(1:10, freq = 7, start = c(12, 2)), calendar = TRUE) # print.ts(.)
## Using July 1954 as start date:
gnp <- ts(cumsum(1 + round(rnorm(100), 2)),
start = c(1954, 7), frequency = 12)
plot(gnp) # using `plot.ts' for time-series plot
## Multivariate
z <- ts(matrix(rnorm(300),100,3),start=c(1961,1), frequency=12)
ts(1:10, frequency = 4, start = c(1959, 2)) # 2nd Quarter of 1959
print( ts(1:10, freq = 7, start = c(12, 2)), calendar = TRUE) # print.ts(.)
## Using July 1954 as start date:
gnp <- ts(cumsum(1 + round(rnorm(100), 2)),
start = c(1954, 7), frequency = 12)
plot(gnp) # using `plot.ts' for time-series plot
## Multivariate
z <- ts(matrix(rnorm(300),100,3),start=c(1961,1), frequency=12)
## A phase plot:
data(nhtemp)
plot(nhtemp, c(nhtemp[-1],NA), cex = .8, col="blue",
main="Lag plot of New Haven temperatures")
## A phase plot:
data(nhtemp)
plot(nhtemp, c(nhtemp[-1],NA), cex = .8, col="blue",
main="Lag plot of New Haven temperatures")