The Time Series Plot for a time series \(Y_t\) for \(t=1, 2, …, T\) with \(T\) observations is simply a Scatter Plot for the data pairs \((Y_t, t)\), i.e. the observations are plotted against the time index \(t\).
The horizontal axis represents the time index \(t\).
The vertical axis shows the values of \(Y_t\).
The Time Series Plot is available on the public website:
The Time Series Plot is also available in RFC (when using the default profile) under the “Time Series / Time Series Plot” menu item.
To compute the Time Series Plot on your local machine, the following script can be used in the R console:
x <- cumsum(rnorm(150))
summary(x)
par4 = 12
ylimmax = ''
ylimmin = ''
ylab = 'value'
xlab = 'time'
main = 'Random Walk'
n <- length(x)
plot(x,col=2,type='b',main=main,xlab=xlab,ylab=ylab,xaxt='n')
axis(1,at=seq(1,n,par4))
grid(nx=0,ny=NULL,col='black')
abline(v=seq(1,n,par4),col='black',lty='dotted')
Min. 1st Qu. Median Mean 3rd Qu. Max.
-13.151 -5.196 -1.332 -1.304 3.987 7.700 To compute the Time Series Plot, the R code uses the plot function from the base R installation.
The Time Series Plot is used to visualise the time series under investigation. Experienced researchers will be able to identify important properties such as non-seasonal and seasonal trends.
The Time Series Plot has the following advantages:
The Time Series Plot has the following disadvantages:
The plot shows the famous Airline time series which exhibits a non-seasonal and a seasonal trend. This time series is used in numerous examples throughout this book.