Abstract
We have until now been concerned mainly with sequences of independent and identically distributed stochastic variables. When we turn to situations in which we believe that either the variables are dependent upon each other or their probability distributions change with time, or both, the mathematical tools take on a quite different appearance. The relevant tool for studying such situations is the theory of random functions, that is, the theory of stochastic processes.
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© 1971 Brown University
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Freiberger, W., Grenander, U. (1971). Stochastic Processes. In: A Course in Computational Probability and Statistics. Applied Mathematical Sciences, vol 6. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-9837-3_4
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DOI: https://doi.org/10.1007/978-1-4612-9837-3_4
Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-90029-2
Online ISBN: 978-1-4612-9837-3
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