An introduction to stochastic modeling

A random field is a mathematical model of evolutional fluctuating complex systems parametrized by a multi-dimensional manifold like a curve or a surface. As the parameter varies, the random field carries much information and hence it has complex stochastic structure. The authors of this text use an approach that is characteristic: namely, they first construct innovation, which is the most elemental stochastic process with a basic and simple way of dependence, and then express the given field as a function of the innovation. They therefore establish an infinite-dimensional stochastic calculus, in particular a stochastic variational calculus. The analysis of functions of the innovation is essentially infinite-dimensional. The authors use not only the theory of functional analysis, but also their new tools for the study Conditional probability and conditional expectation -- Markov chains: introduction -- Long run behavior of markov chains -- Poisson processes -- Continuos time markov chains -- renewal phenomena -- Brownian motion and related processes -- Queueing systems