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N-dimensional RV vs DT Random process

  1. Apr 10, 2010 #1
    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?
     
  2. jcsd
  3. Apr 11, 2010 #2

    mathman

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    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.
     
  4. Apr 11, 2010 #3
    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?
     
  5. Apr 12, 2010 #4

    mathman

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    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.
     
  6. Apr 12, 2010 #5
    Thanks mathman. I think I get it now.
     
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