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Revision as of 07:46, 6 April 2002 by 213.253.40.17 (talk) (removed even more whitespace from text -- what software is the other user using?)(diff) ← Previous revision | Latest revision (diff) | Newer revision → (diff)A stochastic process is a random function. This means that, if
f : D -> R
is a random function with domain D and range R, the image of each point of D, f(x), is a random variable with values in R.
Of course, the mathematical definition of a function includes the case "a function from {1,...,n} to R is a vector in R^n", so multidimensional random variables are a special case of stochastic processes.
For our first infinite example, take the domain to be N, the natural numbers, and our range to be R, the real numbers. Then, a function f : N -> R is a sequence of real numbers, and the following questions arise:
- How is a random sequence specified?
- How do we find the answers to typical questions about sequences, such as
- what is the probability distribution of the value of f(i)?
- what is the probability that f is bounded?
- what is the probability that is f monotonic?
- what is the probability that f(i) has a limit as i->infty?
- if we construct a series from f(i), what is the probability that the series converges? What is the probability distribution of the sum?