Abstract
So far we have studied the probabilistic description of a finite number of random variables. This is useful for random phenomena that have definite beginning and end times. Many physical phenomena, however, are more appropriately modeled as ongoing in time. Such is the case for the annual summer rainfall in Rhode Island as shown in Figure 1.1 and repeated for convenience in Figure 16.1.
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© 2012 Steven M. Kay
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Kay, S.M. (2012). Basic Random Processes. In: Intuitive Probability and Random Processes Using MATLAB®. Springer, Boston, MA. https://doi.org/10.1007/0-387-24158-2_16
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DOI: https://doi.org/10.1007/0-387-24158-2_16
Publisher Name: Springer, Boston, MA
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