Algebraic methods in Markov chains -- Ratio theorems of transition probabilities and applications -- Sums of independent random variables as a Markov chain -- Order statistics, Poisson processes, and applications -- Continuous time Markov chains -- Diffusion processes -- Compounding stochastic processes -- Fluctuation theory of partial sums of independent identically distributed random variables -- Queuing processes.
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SUMMARY OR ABSTRACT
Text of Note
This Second Course continues the development of the theory and applications of stochastic processes as promised in the preface of A First Course. We emphasize a careful treatment of basic structures in stochastic processes in symbiosis with the analysis of natural classes of stochastic processes arising from the biological, physical, and social sciences. -- description from https://books.google.com