Introduction and Summary

  • Julian Keilson
Part of the Applied Mathematical Sciences book series (AMS, volume 28)


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.


Passage Time Markov Chain Model Fundamental Matrix Exit Time Finite Markov Chain 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag New York Inc. 1979

Authors and Affiliations

  • Julian Keilson
    • 1
  1. 1.The University of RochesterRochesterUSA

Personalised recommendations