Elementary methods for failure due to a sequence of Markovian events.
Gani, J. (1998)
Journal of Applied Mathematics and Stochastic Analysis
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Displaying similar documents to “First hitting place probabilities for a discrete version of the Ornstein-Uhlenbeck process.”
Elementary methods for failure due to a sequence of Markovian events.
A simple interpretation of two stochastic processes subject to an independent death process.
Gani, Joseph, Swift, Randall J. (2009)
Applied Mathematics E-Notes [electronic only]
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Markov chain comparison.
Dyer, Martin, Goldberg, Leslie Ann, Jerrum, Mark, Martin, Russell (2006)
Probability Surveys [electronic only]
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Sufficient conditions for torpid mixing of parallel and simulated tempering.
Woodard, Dawn B., Schmidler, Scott C., Huber, Mark (2009)
Electronic Journal of Probability [electronic only]
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A martingale proof of Dobrushin's theorem for non-homogeneous Markov chains.
Sethuraman, S., Varadhan, S.R.S. (2005)
Electronic Journal of Probability [electronic only]
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On variance conditions for Markov chain CLTs.
Häggström, Olle, Rosenthal, Jeffrey S. (2007)
Electronic Communications in Probability [electronic only]
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Markov chain analysis of weekly rainfall data in determining drought-proneness.
Banik, Pabitra, Mandal, Abhyudy, Rahman, M.Sayedur (2002)
Discrete Dynamics in Nature and Society
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Bounding fastest mixing.
Roch, Sébastien (2005)
Electronic Communications in Probability [electronic only]
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Clustering behavior of a continuous-sites stepping-stone model with Brownian migration.
Zhou, Xiaowen (2003)
Electronic Journal of Probability [electronic only]
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Products of stochastic matrices and applications.
Cohn, Harry (1989)
International Journal of Mathematics and Mathematical Sciences
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Partition-dependent stochastic measures and -deformed cumulants.
Anshelevich, Michael (2001)
Documenta Mathematica
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On the Markov chain central limit theorem.
Jones, Galin L. (2004)
Probability Surveys [electronic only]
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Generic properties of learning systems
Tomasz Szarek (2000)
Annales Polonici Mathematici
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It is shown that the set of learning systems having a singular stationary distribution is generic in the family of all systems satisfying the average contractivity condition.