I want to generate a time series that follows an AR(1) process and thus has a certain overall level of autocorrelation.
I'm using the
arima.sim function (which is implemented as standard in R).
I thought that for example the following command:
would generate a time series of length 400 and an autocorrelation of -0.5.
However, I've noticed that the values you can give to the
Ar parameter are not limited to [-1; 1]. For example, you could input
Can anyone explain to me what the
Ar parameter actually represents? Because it apparently is not a correlation coefficient.
After reading on the internet it seems to me that there's not a lot of information there for people who want to simulate time series data using a model as opposed to people who want to fit data to a model.