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Part of the book series: Applied Mathematical Sciences ((AMS,volume 28))

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Abstract

This study has three goals. The first is the presentation of working tools needed to quantify the behavior of finite Markov chains in discrete and continuous time when the chain has many degrees of freedom. Ergodic state probabilities, ergodic flow rates, ruin probabilities, passage time and regeneration time distributions and their moments are of typical interest. Applications are oriented largely to reliability theory and inventory theory, but the methods apply as well to other branches of applied probability.

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© 1979 Springer-Verlag New York Inc.

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Keilson, J. (1979). Introduction and Summary. In: Keilson, J. (eds) Markov Chain Models — Rarity and Exponentiality. Applied Mathematical Sciences, vol 28. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-6200-8_1

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  • DOI: https://doi.org/10.1007/978-1-4612-6200-8_1

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-0-387-90405-4

  • Online ISBN: 978-1-4612-6200-8

  • eBook Packages: Springer Book Archive

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