

   ts {base}                                    R Documentation

   TTiimmee--SSeerriieess OObbjjeeccttss

   DDeessccrriippttiioonn::

        The function `ts' is used to create time-series
        objects.

        `as.ts' and `is.ts' coerce an object to a time-series
        and test whether an object is a time series.

   UUssaaggee::

        ts(data = NA, start = 1, end = numeric(0), frequency = 1,
           deltat = 1, ts.eps = .Options$ts.eps, class, names)
        as.ts(x)
        is.ts(x)

        print(ts.obj, calendar, ...)
        plot(ts.obj, plot.type=c("multiple", "single"), ...)
        lines(ts.obj, ...)

   AArrgguummeennttss::

       data: a vector or matrix of the observed time-series
             values.

      start: the time of the first observation. Either an inte-
             ger which correspond or a vector of two integers,
             which give a natural time unit and a (1-based)
             number of samples into the time unit.

        end: the time of the last observation, specified in the
             same way as `start'.

   frequency: the number of observations per unit of time.

     deltat: the fraction of the sampling period between suc-
             cessive observations; e.g., 1/12 for monthly data.
             Only one of `frequency' or `deltat' should be pro-
             vided.

     ts.eps: time series comparison tolerance.  Frequencies are
             considered equal if their absolute difference is
             less than `ts.eps'.

      class: class to be given to the result, or none if `NULL'
             or `"none"'. The default is `"ts"' for a single
             series, `c("mts", "ts")' for multiple series.

      names: a character vector of names for the series in a
             multiple series: defaults to the colnames of
             `data', or `Series 1', `Series 2', ....

   calendar: enable/disable the display of information about
             month names, quarter names or year when printing.
             The default is `TRUE' for a frequency of 4 or 12,
             `FALSE' otherwise.

   plot.type: for multivariate time series, should the series
             by plotted separately (with a common time axis) or
             on a single plot?

        ...: additional arguments to print or plot.

   DDeettaaiillss::

        The function `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.

        Class `"ts"' has a number of methods. In particular
        arithmetic will attempt to align time axes, and subset-
        ting to extract subsets of series can be used (e.g.
        `EuStockMarkets[, "DAX"]').  However, subsetting the
        first (or only) dimension will return a matrix or vec-
        tor, as will matrix subsetting.

        The value of argument `frequency' is used when the
        series is sampled an integral 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. Values of `4' and `12' are assumed in (e.g.)
        `print' methods to imply a quarterly and monthly series
        respectively.

        `as.ts' will use the `tsp' attribute of the object if
        it has one to set the start and end times and fre-
        quency.

   SSeeee AAllssoo::

        `tsp', `frequency', `start', `end', `time', `window'

        Standard package `ts' for many additional time-series
        functions.

   EExxaammpplleess::

        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)
        plot(z)
        plot(z, plot.type="single", lty=1:3)

        ## A phase plot:
        data(nhtemp)
        plot(nhtemp, c(nhtemp[-1],NA), cex = .8, col="blue",
             main="Lag plot of New Haven temperatures")
        ## a clearer way to do this would be
        library(ts)
        plot(nhtemp, lag(nhtemp,1), cex = .8, col="blue",
             main="Lag plot of New Haven temperatures")

