Monte carlo simulation
Publication Name
Springer Series in Reliability Engineering
Abstract
This chapter discusses the basic concept and techniques for Monte Carlo simulation. The simulation methods for a single random variable as well as those for a random vector (consisting of multiple variables) are discussed, followed by the simulation of some special stochastic processes, including Poisson process, renewal process, Gamma process and Markov process. Some advanced simulation techniques, such as the importance sampling, Latin hypercube sampling, and subset simulation, are also addressed in this chapter.
Open Access Status
This publication is not available as open access
First Page
105
Last Page
163