May 2019
Beginner to intermediate
266 pages
5h 57m
English
Content preview from Hands-On Exploratory Data Analysis with R
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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, na.action = na.contiguous, demean = TRUE,...)
The autocorrelation plot for our dataset with all of the 15 attributes is generated using the following command:
> acf(AirQualityUCI) ...
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