R: Autocorrelation

autcor {timsac} | R Documentation

## Autocorrelation

### Description

Estimate autocovariances and autocorrelations.

### Usage

    autcor(y, lag = NULL, plot = TRUE, lag_axis = TRUE)

### Arguments

`y` | a univariate time series.
`lag` | maximum lag. Default is 2*sqrt(n), where n is the length of the time series `y`.
`plot` | logical. If `TRUE` (default), autocorrelations are plotted.
`lag_axis` | logical. If `TRUE` (default) with plot = `TRUE`, x-axis is drawn.

### Value

`acov` | autocovariances.
`acor` | autocorrelations (normalized covariances).
`mean` | mean of `y`.

### References

H.Akaike and T.Nakagawa (1988) Statistical Analysis and Control of Dynamic Systems. Kluwer Academic publishers.

### Examples

    # Example 1 for the normal distribution
    y <- rnorm(200)
    autcor(y, lag_axis = FALSE)

    # Example 2 for the ARIMA model
    y <- arima.sim(list(order=c(2,0,0), ar=c(0.64,-0.8)), n = 200)
    autcor(y, lag = 20)

[Package timsac version 1.3.6 Index]