acf                    package:ts                    R Documentation

Autocovariance and Autocorrelation Function Estimation

Description:

     The function `acf' computes (and by default plots) estimates of
     the autocovariance or autocorrelation function.  Function `pacf'
     is the function used for the partial autocorrelations.  Function
     `ccf' computes the cross-correlation or cross-covariance of two
     univariate series.

Usage:

     acf(x, lag.max = NULL,
         type = c("correlation", "covariance", "partial"),
         plot = TRUE, na.action = na.fail, demean = TRUE, ...)
     pacf(x, lag.max = NULL, plot = TRUE, na.action = na.fail, ...)
     ccf(x, y, lag.max = NULL, type = c("correlation", "covariance"),
         plot = TRUE, na.action = na.fail, ...)

Arguments:

    x, y: a univariate or multivariate (not `ccf') time series object
          or a numeric vector or matrix.

 lag.max: maximum number of lags at which to calculate the acf. Default
          is 10*log10(N) where N is the number of observations.

    type: character string giving the type of acf to be computed.
          Allowed values are `"correlation"' (the default),
          `"covariance"' or `"partial"'.

    plot: logical. If `TRUE' the acf is plotted.

na.action: function to be called to handle missing values.

  demean: logical.  Should the covariances be about the sample means?

     ...: further arguments to be passed to `plot.acf'.

Details:

     For `type' = `"correlation"' and `"covariance"', the estimates are
     based on the sample covariance.

     The partial correlation coefficient is estimated by fitting
     autoregressive models of successively higher orders up to
     `lag.max'.

     The generic function `plot' has a method for objects of class
     `"acf"'.

     The lag is returned and plotted in units of time, and not numbers
     of observations.

Value:

     An object of class `"acf"', which is a list with the following
     elements:

     lag: A three dimensional array containing the lags at which the
          acf is estimated.

     acf: An array with the same dimensions as `lag' containing the
          estimated acf.

    type: The type of correlation (same as the `type' argument).

  n.used: The number of observations in the time series.

  series: The name of the series `x'.

  snames: The series names for a multivariate time series.


     The result is returned invisibly if `plot' is `TRUE'.

Author(s):

     Original: Paul Gilbert, Martyn Plummer. Extensive modifications
     and univariate case of `pacf' by B.D. Ripley.

See Also:

     `plot.acf'

Examples:

     ## Examples from Venables & Ripley
     data(lh)
     acf(lh)
     acf(lh, type = "covariance")
     pacf(lh)

     data(UKLungDeaths)
     acf(ldeaths)
     acf(ldeaths, ci.type = "ma")
     acf(ts.union(mdeaths, fdeaths))
     ccf(mdeaths, fdeaths) # just the cross-correlations.

