Monte carlo and quasi-monte carlo methods 2006 / by International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing (7th : 2006 : Ulm, Germany), Keller, Alexander, 1968-, Heinrich, Stefan, Niederreiter, Harald, 1944-

Quasi-Monte Carlo methods applied to tau-leaping in stochastic biological systems by Beentjes, C, Baker, R

“…Quasi-Monte Carlo methods have proven to be effective extensions of traditional Monte Carlo methods in, amongst others, problems of quadrature and the sample path simulation of stochastic differential equations. …”

Multilevel and Quasi Monte Carlo methods for the calculation of the Expected Value of Partial Perfect Information by Fang, W, Wang, Z, Giles, MB, Jackson, C, Welton, N, Andrieu, C, Thom, H

An efficient quasi-Monte Carlo method with forced fixed detection for photon scatter simulation in CT. by Guiyuan Lin, Shiwo Deng, Xiaoqun Wang

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An efficient quasi-Monte Carlo method with forced fixed detection for photon scatter simulation in CT by Guiyuan Lin, Shiwo Deng, Xiaoqun Wang

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Pricing of Arithmetic Average Asian Option by Combining Variance Reduction and Quasi-Monte Carlo Method by Lingling Xu, Hongjie Zhang, Fu Lee Wang

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Variance reduction for generalized likelihood ratio method by conditional Monte Carlo and randomized Quasi-Monte Carlo methods by Yijie Peng, Michael C. Fu, Jiaqiao Hu, Pierre L’Ecuyer, Bruno Tuffin

“…Moreover, we combine GLR with conditional Monte Carlo methods and randomized quasi-Monte Carlo methods to reduce the variance. Numerical experiments show that variance reduction could be significant in various applications.…”
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Multilevel quasi Monte Carlo methods for elliptic PDEs with random field coefficients via fast white noise sampling by Croci, M, Giles, M, Farrell, PE

Optimizing Air Pollution Modeling with a Highly-Convergent Quasi-Monte Carlo Method: A Case Study on the UNI-DEM Framework by Venelin Todorov, Slavi Georgiev, Ivan Georgiev, Snezhinka Zaharieva, Ivan Dimov

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Variability Analysis of the Hysteretic Behavior of Fiber-Reinforced Polymer (FRP)-Confined Concrete Columns Based on a Secondary Development Model by Yuanfeng Wang, Lei Pan, Weitao Niu, Kai Li, Kun Guo

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Uncertainpy: A Python Toolbox for Uncertainty Quantification and Sensitivity Analysis in Computational Neuroscience by Simen Tennøe, Simen Tennøe, Geir Halnes, Geir Halnes, Gaute T. Einevoll, Gaute T. Einevoll, Gaute T. Einevoll

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Monte Carlo Methods and the Koksma-Hlawka Inequality by Sergey Ermakov, Svetlana Leora

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ESTIMASI VALUE AT RISK PORTOFOLIO MENGGUNAKAN METODE QUASI MONTE CARLO DENGAN PEMBANGKIT BILANGAN ACAK HALTON by PUTU SAVITRI DEVI, KOMANG DHARMAWAN, LUH PUTU IDA HARINI

“…The purpose of this study is to estimate the risk of a portfolio represented as a VaR where the volatilities were simulated by th the Monte Carlo and Quasi Monte Carlo methods. The Monte Carlo method involves generating random numbers and the Quasi Monte Carlo method uses Halton's quasi-random sequences. …”
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Valuation of Discrete Barrier American Options by Carlos Patrício Samanez, Giuliano Carroza Uzêda Iorio de Souza

“…The developed model consists of an adaptation of the method of Grant, Vora and Weeks (1997), in order to allow to incorporate the barriers. The Hybrid Quasi-Monte Carlo method was used in the simulations and the Bisection method in the definition of the options trigger curves. …”
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Introduction to vector quantization and its applications for numerics* by Pagès Gilles

“…A brief comparison with Quasi-Monte Carlo method is also carried out.…”
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Quasi-Monte Carlo simulation of Brownian sheet with application to option pricing by Xinyu Song, Yazhen Wang

“…Monte Carlo and quasi-Monte Carlo methods are widely used in scientific studies. …”
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A Review of Representative Points of Statistical Distributions and Their Applications by Kai-Tai Fang, Jianxin Pan

“…In this paper we give a review of the three main methods for constructing RPs, namely based on the Monte Carlo method, the number-theoretic method (or quasi-Monte Carlo method), and the mean square error method, aiming to introduce such important methods to the statistical or mathematical community. …”
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Reliability and power supply capability evaluation of active distribution networks with four-terminal soft open points by Feng Yan, Xiangyan Chen, Wensheng Tang, Ri Yan, Hao Wu

“…Then, using the feeder partition method, the effects of four-terminal SOPs on the power outage duration of different load areas after a fault are studied, and the reliability evaluation process for ADNs with four-terminal SOPs is developed based on the quasi-Monte Carlo method. Later, with reliability as the main constraint, the power supply capability evaluation model for ADNs with four-terminal SOPs is established, and the solution algorithm is proposed. …”
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Constructions of low-discrepancy point sets and sequences. by Yeo, Anderson Siang Jing.

“…Low-discrepancy point sets and sequences play an important role in quasi-Monte Carlo method for numerical integration. They provide good quadrature points for estimating the de nite integrals of functions that cannot be integrated analytically. …”
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Quasi-Monte Carlo for finance applications. by Giles, M, Kuo, F, Sloan, I, Waterhouse, B

“…Our aim is to provide a starting point for finance practitioners new to quasi-Monte Carlo methods.…”