Chapman and Hall, 1980. — 187 p. — ISBN: 978-0412219108, 0412219107. Theoretical framework; Special models; Operations on point processes; Multivariate point processes; Spatial processes.
Springer, 2008. — 590 p. Stochastic point processes are sets of randomly located points in time, on the plane or in some general space. This book provides a general introduction to the theory, starting with simple examples and an historical overview, and proceeding to the general theory. It thoroughly covers recent work in a broad historical perspective in an attempt to provide a...
Springer, 2005. — 186 p. — ISBN: 9783540234517, 3540234519. This book provides a rigorous but elementary introduction to the theory of Markov Processes on a countable state space. It should be accessible to students with a solid undergraduate background in mathematics, including students from engineering, economics, physics, and biology. Topics covered are: Doeblin's theory,...
Elsevier Science Publishers, 1990. - 723p. One of the central problems in operations research and management science is how to quantify the effects of uncertainty about the future. This, the second volume in a series of handbooks, is devoted to models where chance events play a major role. The thirteen chapters survey topics in applied probability that have been particularly...
Springer, 2009. — 451 p. Stochastic processes are mathematical models of random phenomena that evolve according to prescribed dynamics. Processes commonly used in applications are Markov chains in discrete and continuous time, renewal and regenerative processes, Poisson processes, and Brownian motion. This volume gives an in-depth description of the structure and basic properties...