In the next example, we will show you auto-correlation. First, we upload an R package called astsa, which stands for Applied Statistical Time Series Analysis. Then, we upload the US GDP with quarterly frequency:
library(astsa)path<-"http://canisius.edu/~yany/RData/"dataSet<-"usGDPquarterly"con<-paste(path,dataSet,".RData",sep='')load(url(con))x<-.usGDPquarterly$DATEy<-.usGDPquarterly$GDP_CURRENTplot(x,y)diff4 = diff(y,4)acf2(diff4,24)
In the preceding program, the diff() function takes a difference, such as the current value minus the previous value. The second input value indicates the lag. The function called acf2() is used to plot and print the ACF and PACF of a time series. ACF stands for auto-covariance function, while PACF ...
