Data visualization

In this section, we will focus on the creation of the following plots:

• Autocorrelation
• Spectrum
• Phase

Autocorrelation plots

Autocorrelation plots are regarded as plots for creating randomness in a particular dataset. This randomness is very powerful regarding autocorrelations of data values with varying time lags. It is mandatory that autocorrelations for any dataset should be near zero, for any and all time-lag separations.

The Acf function computes (and, by default, plots) an estimate of the autocorrelation function of a (possibly multivariate) time series. The syntax is as follows:

> Acf(x, lag.max = NULL, type = c("correlation", "covariance","partial"), plot = TRUE...