| Review: |
This is a self-contained practical entry-level text on stochastic processes and control for jump diffusions in continuous time – technically, Markov processes in continuous time. The first four chapters cover the basics for simple jump-diffusions, i.e. stochastic jump diffusion (Weiner or Brownian motion) and a simple Poisson-driven processes, including stochastic integration based on Itô’s computationally motivated mean-square convergence for Markov processes and stochastic calculus for transformations of stochastic differential equations (SDEs). The next eight chapters deal with special topics, and can be dipped into according to the reader’s interest. They include: Space-time Poisson, State-dependent Noise and Multidimensions; Stochastic Optimal Control: Stochastic Dynamic Programming; Kolmogorov Forward and Backward Equations and their Applications; Computational Stochastic Control Methods; Stochastic Simulations; Applications in Financial Engineering; Applications in Mathematical Biology and Medicine; : and Applied Guide to Abstract Theory of Stochastic Processes. |