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.
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.
Howard E. Taylor is a research chemist with the National Research Program, Water Resources Division, U.S. Geological Survey located in Boulder, Colorado. Dr. Taylor has played a major role over the past 25 years in the development of plasma spectrometric techniques in analytical chemistry, as reflected in his more than 150 technical publications and the presentation of numerous papers at national and international technical meetings. He has served as faculty affiliate at Colorado State University and has taught American Chemical Society Short Courses for more than 15 years.
Inhaltsangabe
Preface. Preface to A First Course. Preface to First Edition. Contents of A First Course. 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. Queueing Processes. Miscellaneous Problems. Index.
Preface. Preface to A First Course. Preface to First Edition. Contents of A First Course. 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. Queueing Processes. Miscellaneous Problems. Index.
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