N-dimensional RV vs DT Random process

[dionysian]

If a discrete random process can be viewed as a collection of random variables indexed by a value n and a discrete N dimensional random variable can be viewed as N random variables with with a joint pmf. In these cases it seems like there is not much difference between a N dimensional random variable and a discrete time random process.

Know i am sure I am missing something very subtle but important here. I geuss me question is how is a discrete time random process diffrent than a n deminsional random varible?

 

[mathman]

The difference is primary how they are handled. A sequence (for example) might be treated as a Markov process, where each variable is dependent on the value of the previous trial, but none before that. Also when dealing with a sequence, there is no limit on the number of terms, while treating it in n dimensions usually means the vector is studied as one entity.

 

[dionysian]

Thanks for your reply mathman. So the two are very similar but they are just interpreted diffrently? Is there any diffrence other than that which someone might know about?

 

[mathman]

I can't fully understand your second question, but the point is there is nothing other than how I described it. Context is the main point.

 

[dionysian]

Thanks mathman. I think I get it now.