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Theory & Method

Run Probabilities in Sequences of Markov-Dependent Trials

Pages 168-175 | Received 01 Dec 1981, Published online: 12 Mar 2012

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Anastasios N. Arapis, Frosso S. Makri & Zaharias M. Psillakis. (2018) Distributions of statistics describing concentration of runs in non homogeneous Markov-dependent trials. Communications in Statistics - Theory and Methods 47:9, pages 2238-2250.
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Xiaoyan Zhu & Mahmoud Boushaba. (2017) A linear weighted (, , ) system for non-homogeneous Markov-dependent components. IISE Transactions 49:7, pages 722-736.
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BONIFACIO FERNÁNDEZ L.ANDRÉS VERGARA G.. (1998) Risk of scarcity of monthly precipitation and streamflows in semiarid regions. Hydrological Sciences Journal 43:5, pages 759-773.
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W.Y. Wendy Lou. (1996) On Runs and Longest Run Tests: A Method of Finite Markov Chain Imbedding. Journal of the American Statistical Association 91:436, pages 1595-1601.
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J.C. Fu & M.V. Koutras. (1994) Distribution Theory of Runs: A Markov Chain Approach. Journal of the American Statistical Association 89:427, pages 1050-1058.
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Gail Rubin, CharlesE. McCulloch & MichaelA. Shapiro. (1990) Multinomial Runs Tests to Detect Clustering in Constrained Free Recall. Journal of the American Statistical Association 85:410, pages 315-320.
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Mark F. Schilling. (1990) The Longest Run of Heads. The College Mathematics Journal 21:3, pages 196-207.
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StevenJ. Schwager. (1984) Bonferroni Sometimes Loses. The American Statistician 38:3, pages 192-197.
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