AbstractSequences of points with a low discrepancy are the basic building blocks for quasi-Monte Carlo methods. Traditionally these points are generated in a unit cube.To develop point sets on a simplex we will transform the low-discrepancy points from the unit cube to a simplex. An advantage of this approach is that most of the known results on low-discrepancy sequences can be re-used. After introducing several transformations, their efficiency as well as their quality will be evaluated. We present a Koksma–Hlawka inequality which says that under certain conditions the order of convergence using the new point set is the same as that of the original set
The Monte Carlo method is one of the widely used numerical methods for simulating probability distri...
AbstractPolynomial lattice point sets are polynomial versions of classical lattice point sets and am...
In a recent paper [1], we used a linear recurrence of order r over F2w, the finite field with 2w ele...
AbstractSequences of points with a low discrepancy are the basic building blocks for quasi-Monte Car...
International audienceThe class of $(t,m,s)$-nets and $(t,s)$-sequences, introduced in their most ge...
International audienceThe class of $(t,m,s)$-nets and $(t,s)$-sequences, introduced in their most ge...
AbstractThe concepts of (t,m,s)-nets and (t,s)-sequences are among the best known classes of point s...
AbstractWe generalize and improve earlier constructions of low-discrepancy sequences by Sobol', Faur...
Low-discrepancy point sets and sequences play an important role in quasi-Monte Carlo method for n...
summary:Many low-discrepancy sets are suitable for quasi-Monte Carlo integration. Skriganov showed t...
Summary. This article presents a survey of low-discrepancy sequences and their applications to quasi...
AbstractWe provide a deterministic algorithm that constructs small point sets exhibiting a low star ...
We introduce two novel techniques for speeding up the generation of digital \((t,s)\)-sequences. Bas...
Theme 1 - Reseaux et systemes. Projet ModelSIGLEAvailable at INIST (FR), Document Supply Service, un...
International audienceIn this paper, we derive new general upper bounds on the star discrepancy of (...
The Monte Carlo method is one of the widely used numerical methods for simulating probability distri...
AbstractPolynomial lattice point sets are polynomial versions of classical lattice point sets and am...
In a recent paper [1], we used a linear recurrence of order r over F2w, the finite field with 2w ele...
AbstractSequences of points with a low discrepancy are the basic building blocks for quasi-Monte Car...
International audienceThe class of $(t,m,s)$-nets and $(t,s)$-sequences, introduced in their most ge...
International audienceThe class of $(t,m,s)$-nets and $(t,s)$-sequences, introduced in their most ge...
AbstractThe concepts of (t,m,s)-nets and (t,s)-sequences are among the best known classes of point s...
AbstractWe generalize and improve earlier constructions of low-discrepancy sequences by Sobol', Faur...
Low-discrepancy point sets and sequences play an important role in quasi-Monte Carlo method for n...
summary:Many low-discrepancy sets are suitable for quasi-Monte Carlo integration. Skriganov showed t...
Summary. This article presents a survey of low-discrepancy sequences and their applications to quasi...
AbstractWe provide a deterministic algorithm that constructs small point sets exhibiting a low star ...
We introduce two novel techniques for speeding up the generation of digital \((t,s)\)-sequences. Bas...
Theme 1 - Reseaux et systemes. Projet ModelSIGLEAvailable at INIST (FR), Document Supply Service, un...
International audienceIn this paper, we derive new general upper bounds on the star discrepancy of (...
The Monte Carlo method is one of the widely used numerical methods for simulating probability distri...
AbstractPolynomial lattice point sets are polynomial versions of classical lattice point sets and am...
In a recent paper [1], we used a linear recurrence of order r over F2w, the finite field with 2w ele...