Results 231 to 240 of about 12,230 (257)
Some of the next articles are maybe not open access.
2015
There are many scientific as well as real-world applications where we run into the problem of computing a definite integral. In calculus courses you are taught that a definite integral \(\int _{a}^{b}f(u)du\) is evaluated by the fundamental theorem of integral calculus which says that $$\displaystyle{ \int _{a}^{b}f(u)du = F(b) - F(a), }$$ (4.1)
Harald Niederreiter, Arne Winterhof
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There are many scientific as well as real-world applications where we run into the problem of computing a definite integral. In calculus courses you are taught that a definite integral \(\int _{a}^{b}f(u)du\) is evaluated by the fundamental theorem of integral calculus which says that $$\displaystyle{ \int _{a}^{b}f(u)du = F(b) - F(a), }$$ (4.1)
Harald Niederreiter, Arne Winterhof
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Monte Carlo and Quasi-Monte Carlo Methods
2020Monte 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. This article presents an introduction to Monte Carlo methods for integration problems, including convergence theory, sampling methods and variance reduction ...
Tuffin, Bruno, L'Écuyer, Pierre
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Progress in Nuclear Energy, 1990
Abstract A systematic approach is presented to quasi-random numbers that being used instead of random numbers in Monte Carlo algorithms imply their convergence in the classical sense. The rate of convergence of quasi-Monte Carlo algorithms may be almost 1/N (here N is the number of trials).
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Abstract A systematic approach is presented to quasi-random numbers that being used instead of random numbers in Monte Carlo algorithms imply their convergence in the classical sense. The rate of convergence of quasi-Monte Carlo algorithms may be almost 1/N (here N is the number of trials).
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Monte Carlo and Quasi-Monte Carlo Methods
2013Chapter 12 discusses Monte Carlo and quasi-Monte Carlo methods and demonstrates how these techniques can be used to compute functionals of multidimensional diffusions. Monte Carlo methods feature prominently in this book, in particular we discuss how to use Lie Symmetry methods to construct unbiased Monte Carlo estimators in Chap. 6, and we discuss how
Jan Baldeaux, Eckhard Platen
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2018
In this chapter we present the so-called Quasi-Monte Carlo (QMC) method, which can be seen as a deterministic alternative to the standard Monte Carlo method: the pseudo-random numbers are replaced by deterministic computable sequences of \([0,1]^d\)-valued vectors which, once substituted mutatis mutandis in place of pseudo-random numbers in the Monte ...
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In this chapter we present the so-called Quasi-Monte Carlo (QMC) method, which can be seen as a deterministic alternative to the standard Monte Carlo method: the pseudo-random numbers are replaced by deterministic computable sequences of \([0,1]^d\)-valued vectors which, once substituted mutatis mutandis in place of pseudo-random numbers in the Monte ...
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Quasi-Monte Carlo Methods in Finance [PDF]
Proceedings of the 2004 Winter Simulation Conference, 2004., 2005 openaire +1 more source
Quasi-Monte Carlo Methods in Numerical Finance
Management Science, 1996Ken Seng Tan, Phelim P Boyle
exaly
High-Performance Quasi-Monte Carlo Financial Simulation
ACM Transactions on Reconfigurable Technology and Systems, 2010Khaled Benkrid
exaly