# Why the Monte Carlo method is so important today

@article{Kroese2014WhyTM, title={Why the Monte Carlo method is so important today}, author={Dirk P. Kroese and Tim J. Brereton and Thomas Taimre and Zdravko I. Botev}, journal={Wiley Interdisciplinary Reviews: Computational Statistics}, year={2014}, volume={6}, pages={386-392} }

Since the beginning of electronic computing, people have been interested in carrying out random experiments on a computer. Such Monte Carlo techniques are now an essential ingredient in many quantitative investigations. Why is the Monte Carlo method MCM so important today? This article explores the reasons why the MCM has evolved from a 'last resort' solution to a leading methodology that permeates much of contemporary science, finance, and engineering. WIREs Comput Stat 2014, 6:386-392. doi… Expand

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#### References

SHOWING 1-10 OF 65 REFERENCES

Monte Carlo methods

- Computer Science
- 2013

The basic principles and the most common Monte Carlo algorithms are reviewed, among which rejection sampling, importance sampling and Monte Carlo Markov chain (MCMC) methods are reviewed. Expand

Simulation and the Monte Carlo Method (Wiley Series in Probability and Statistics)

- Computer Science
- 1981

The authoritative resource for understanding the power behind Monte Carlo Methods and a new co-author has been added to enliven the writing style and to provide modern day expertise on new topics. Expand

Handbook of Monte Carlo Methods

- Mathematics
- 2011

A comprehensive overview of Monte Carlo simulation that explores the latest topics, techniques, and real-world applications
More and more of today’s numerical problems found in engineering and… Expand

Monte Carlo strategies in scientific computing

- Computer Science
- 2001

This book provides a self-contained and up-to-date treatment of the Monte Carlo method and develops a common framework under which various Monte Carlo techniques can be "standardized" and compared. Expand

Simulation and the Monte Carlo method

- Computer Science, Mathematics
- Wiley series in probability and mathematical statistics
- 1981

THE BEGINNING of the MONTE CARLO METHOD

T he year was 1945. Two earth-shaking events took place: the successful test at Alamogordo and the building of the first electronic computer. Their combined impact was to modify qualitatively the… Expand

Monte Carlo and quasi-Monte Carlo methods

- Mathematics
- 1998

Monte Carlo is one of the most versatile and widely used numerical methods. Its convergence rate, O ( N −1/2 ), is independent of dimension, which shows Monte Carlo to be very robust but also slow.… Expand

Multilevel Monte Carlo Path Simulation

- Mathematics, Computer Science
- Oper. Res.
- 2008

We show that multigrid ideas can be used to reduce the computational complexity of estimating an expected value arising from a stochastic differential equation using Monte Carlo path simulations. In… Expand

Fast Sequential Monte Carlo Methods for Counting and Optimization

- Computer Science
- 2013

A comprehensive account of the theory and application of Monte Carlo methodsBased on years of research in efficient Monte Carlo methods for estimation of rare-event probabilities, counting problems,… Expand

Nonuniversal critical dynamics in Monte Carlo simulations.

- Physics, Medicine
- Physical review letters
- 1987

A new approach to Monte Carlo simulations is presented, giving a highly efficient method of simulation for large systems near criticality. The algorithm violates dynamic universality at second-order… Expand