

   TTiimmee--SSeerriieess OObbjjeeccttss

        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, ...)

   AArrgguummeennttss::

       data: a vector or matrix the observed time-series val-
             ues.

      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 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'.

   DDeessccrriippttiioonn::

        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.

        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 corre-
        spond to natural time units, or vectors of two inte-
        gers, 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.

   SSeeee AAllssoo::

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

   EExxaammpplleess::

        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")

