Develops an introductory and relatively simple account of the theory and application of the evolutionary type of stochastic process. Professor Bailey adopts the heuristic approach of applied mathematics and develops both theoretical principles and applied techniques simultaneously.
• Generating Functions.
• Recurrent Events.
• Random Walk Models.
• Markov Chains.
• Discrete Branching Processes.
• Markov Processes in Continuous Time.
• Homogeneous Birth and Death Processes.
• Some Non-Homogeneous Processes.
• Multi-Dimensional Processes.
• Queueing Processes.
• Epidemic Processes.
• Competition and Predation.
• Diffusion Processes.
• Approximations to Stochastic Processes.
• Some Non-Markovian Processes.
• Solutions to Problems.