Stochastic Processes: Problem Solvers, cartea 14

1 What is a Stochastic Process?.- 2 Results from Probability Theory.- 2.1 Introduction to probability theory.- 2.2 Bivariate distributions.- 2.3 Multivariate distributions.- 2.4 Probability generating functions.- 2.5 Characteristic functions.- 3 The Random Walk.- 3.1 The unrestricted random walk.- 3.2 Types of stochastic process.- 3.3 The gambler’s ruin.- 3.4 Generalisations of the random-walk model.- 4 Markov Chains.- 4.1 Definitions.- 4.2 Equilibrium distributions.- 4.3 Applications.- 4.4 Classification of the states of a Markov chain.- 5 The Poisson Process.- 6 Markov Chalns with Continuous Time Parameters.- 6.1 The theory.- 6.2 Applications.- 7 Non-Markov Processes in Continuous Time with Discrete State Spaces.- 7.1 Renewal theory.- 7.2 Population processes.- 7.3 Queuing theory.- 8 Diffusion Processes.- Recommendations For Further Reading.