

ts {base}                                    R Documentation

_T_i_m_e_-_S_e_r_i_e_s _O_b_j_e_c_t_s

_D_e_s_c_r_i_p_t_i_o_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_s_a_g_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_r_g_u_m_e_n_t_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_e_t_a_i_l_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_e_e _A_l_s_o_:

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

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

_E_x_a_m_p_l_e_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")

