A stochastic process is specified by properties of the joint distribution for those random variables. Examples:
- the random variables are independently and identically distributed (iid).
- the process is a Markov process
- the process is a martingale
- the process is white noise
- the process is autoregressive (e.g. AR(1))
- the process has a moving average (e.g. see MA(1))
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