gives conditions for the process proc to be weakly stationary.
Examplesopen allclose all
Basic Examples (3)
Check if an ARProcess is weakly stationary:
Check if the mean function is constant in time:
Check if the covariance function is a function of time difference:
Compare covariance functions of stationary and nonstationary OrnsteinUhlenbeckProcess:
Visualize conditions for an ARProcess to be weakly stationary:
Find a weakly stationary ARProcess:
Some processes known to be non-weakly stationary:
Properties & Relations (4)
Every MAProcess without fixed initial conditions is weakly stationary:
Time series processes with fixed initial conditions are not weakly stationary:
The conditions for an ARMAProcess to be weakly stationary depend only on the autoregressive parameters:
ARIMAProcess may be weakly stationary:
Wolfram Research (2012), WeakStationarity, Wolfram Language function, https://reference.wolfram.com/language/ref/WeakStationarity.html.
Wolfram Language. 2012. "WeakStationarity." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/ref/WeakStationarity.html.
Wolfram Language. (2012). WeakStationarity. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/WeakStationarity.html