Title: Monte Carlo Simulations Of Random Variables, Sequences And Processes
Description: The main goal of analysis in this book are Monte Carlo simulations of Markov processes such as Markov chains (discrete time), Markov jump processes (discrete state space, homogeneous and non-homogeneous), Brownian motion with drift and generalized diffusion with drift (associated to the differential operator of Reynolds equation). Most of these processes can be simulated by using their representations in terms of sequences of independent random variables such as uniformly distributed, exponential and normal variables. There is no available representation of this type of generalized diffusion in spaces of the dimension larger than 1. A convergent class of Monte Carlo methods is described in details for generalized diffusion in the two-dimensional space.
Subjects: Random variables, Simulation, Stochastic processes, Probabilities, Mathematical statistics, Markov processes, Markov Chains, Diffusion processes, Brownian motion, Measure theory, Monte-Carlo-Simulation, Distribution (Probability theory), Stationary processes