Some current issues in quasi-Monte Carlo methods
β Scribed by Harald Niederreiter
- Publisher
- Elsevier Science
- Year
- 2003
- Tongue
- English
- Weight
- 122 KB
- Volume
- 19
- Category
- Article
- ISSN
- 0885-064X
No coin nor oath required. For personal study only.
β¦ Synopsis
We briefly discuss the following issues in quasi-Monte Carlo methods: error bounds and error reduction, optimization of net constructions, and randomization and derandomization.
π SIMILAR VOLUMES
## Quasi-Monte Carlo random search is useful in nondifferentiable optimization. Borrowing ideas of population evolution from genetic algorithms, we introduce an adaptive random search in quasi-Monte Carlo methods (AQMC) for global optimization. Adaptive technique is used such that local search can
Monte Carlo methods, in particular Markov chain Monte Carlo methods, have become increasingly important as a tool for practical Bayesian inference in recent years. A wide range of algorithms is available, and choosing an algorithm that will work well on a speci"c problem is challenging. It is theref