Data used in Chapter 6 Problems
The format is: Time-Series [1:100] with NA for missing values.
Simulated AR(1) with \(\phi=.9\) and \(\sigma_w=1\) and ~10% of the values missing at random (in this case, there happen to be 15 missing values). A similar data set can be generated as follows:
x = sarima.sim(ar=.9, n=100)
u = sample(c(NA,0), replace=TRUE, size=100, prob=c(.1,.9))
arm = x + u
Another approach if you want exactly 10 missing values is this:
arms = sarima.sim(ar=.9, n=100)
arms[sample(1:100, size=10)] = NA
You can find demonstrations of astsa capabilities at FUN WITH ASTSA.
The most recent version of the package can be found at https://github.com/nickpoison/astsa/.
In addition, the News and ChangeLog files are at https://github.com/nickpoison/astsa/blob/master/NEWS.md.
The webpages for the texts and some help on using R for time series analysis can be found at https://nickpoison.github.io/.