Thanks for the suggestion Neil,
I apologize for any possible confusions. Ill post an example. The nature of the question is to solve difference equations, in time, with a stochastic disturbance. In other words just solving for the particular solutions and all homogenous solutions to an SDE (stochastic difference equation). I believe on Mathematica this is referenced instead as a recurrence equation. As an example:
Suppose an AR(1):
$$ \alpha_o + \beta_1 X_{t-1} + \epsilon_t = y_t $$
The solution to this would follow the null solution and the particular solutions. Regardless of which however I have to have a way to set the random parameter
$ \epsilon_t $.
This is of course for pure conceptual and analytical understanding of the solutions behind ARMA process'. As far as I know, I'm not sure to it's direct application. But functionally an ARMA or AR process has a solution. I'm looking for how to derive to that solution but with an error added.
As an added example of what I managed to get correct. I got a solution to a difference equation specified as follows:
$$ RSolveValue[ y[t] == \alpha + \beta_1 x[t-1] + \beta_2 x[t-2], y[t], t] $$
This actually got me very close, if not exactly what I was looking for. But I had to truncate the equation so as to not contain the random disturbance term
$ \epsilon_t $
Again any help is greatly appreciated.
Thanks,
Ali