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Autoregressive Moving-Average Generator

​
random seed
AR terms
0
1
2
3
4
5
weak stationarity condition
T
200
MA terms
0
1
2
3
4
5
approximate cut-off point bounds
​
​
process
correlations
​
​
y
t
= -0.067
y
t-1
-0.663
ϵ
t-1
+
ϵ
t
The autoregressive moving-average process (ARMA) is a discrete-time and continuous-state random process. This generator randomly chooses parameters of the model from the interval
(-1,1)
; you can set the condition for (weak) stationarity.
Part of the output includes the autocorrelation function (ACF), partial autocorrelation function (PACF), and their samples (SACF, SPACF), which serve as a basic tool for model identification in the Box–Jenkins approach by looking for so-called cut-off points.
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