An adaptive Monte Carlo integration algorithm with general division approach

Authors:
Mahmoud H. Alrefaei;Houssam M. Abdul-Rahman
Affiliations:
Qatar University, Department of Mathematics and Physics, PO Box 2713, Doha, Qatar;Jordan University of Science & Technology, Department of Mathematics and Statistics, PO Box 3030, Irbid 22110, Jordan
Venue:
Mathematics and Computers in Simulation
Year:
2008

Citing 5
Cited 1

Implementation of Monte Carlo integration for the analysis of product-form queueing networks

Performance Evaluation
Mersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generator

ACM Transactions on Modeling and Computer Simulation (TOMACS) - Special issue on uniform random number generation
Simulation and the Monte Carlo Method

Simulation and the Monte Carlo Method
An Introduction to Computer Simulation

An Introduction to Computer Simulation
A comparison between (quasi-)Monte Carlo and cubature rule based methods for solving high-dimensional integration problems

Mathematics and Computers in Simulation - Special issue: 3rd IMACS seminar on Monte Carlo methods - MCM 2001

Probabilistic constraints for nonlinear inverse problems

Constraints

Quantified Score

Hi-index	0.00

Visualization

Abstract

We propose an adaptive Monte Carlo algorithm for estimating multidimensional integrals over a hyper-rectangular region. The algorithm uses iteratively the idea of separating the domain of integration into 2^ssubregions. The proposed algorithm can be applied directly to estimate the integral using an efficient way of storage. We test the algorithm for estimating the value of a 30-dimensional integral using a two-division approach. The numerical results show that the proposed algorithm gives better results than using one-division approach.