A note on runs of geometrically distributed random variables |
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Authors: | Serkan Eryilmaz |
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Institution: | Department of Mathematics, Izmir University of Economics, 35330 Balçova, ?zmir, Turkey |
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Abstract: | Recently, Grabner et al. Combinatorics of geometrically distributed random variables: run statistics, Theoret. Comput. Sci. 297 (2003) 261-270] and Louchard and Prodinger Ascending runs of sequences of geometrically distributed random variables: a probabilistic analysis, Theoret. Comput. Sci. 304 (2003) 59-86] considered the run statistics of geometrically distributed independent random variables. They investigated the asymptotic properties of the number of runs and the longest run using the corresponding probability generating functions and a Markov chain approach. In this note, we reconsider the asymptotic properties of such statistics using another approach. Our approach of finding the asymptotic distributions is based on the construction of runs in a sequence of m-dependent random variables. This approach enables us to find the asymptotic distributions of many run statistics via the theorems established for m-dependent sequence of random variables. We also provide the asymptotic distribution of the total number of non-decreasing runs and the longest non-decreasing run. |
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Keywords: | Asymptotic distribution Geometric random variables m-dependent random variables Runs |
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