Quasi-random (also called low discrepancy) sequences are a deterministic alternative to random sequences for use in Monte Carlo methods, such as integration and particle simulations of transport processes. The error in uniformity for such a sequence of N points in the s-dimensional unit cube

Abstract. Quasi-random (also called low discrepancy) sequences are a deterministic alternative to random sequences for use in Monte Carlo methods, such as integration and particle simulations of transport processes. The error in uniformity for such a sequence ofN points in the s-dimensional unit

It is now known that many properties of the objects in certain combinatorial structures are equivalent, in the sense that any object possessing any of the properties must of necessity possess them all. These properties, termed quasirandom, have been described for a variety of structures

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convergence rate. The standard rejection method involves discontinuities, corresponding to the decision to accept or reject. In place of this, a smoothed rejection method is formulated and found to be very effective when used with quasi-random sequences. Monte Carlo evaluation of Feynman-Kac path integrals

Abstract: In recent years, quasi-Monte Carlo (QMC) integration methods have been successfully used in place of Monte-Carlo methods in many applications. However, in practice, QMC integration is often applied to integrands on unbounded domains with non-uniform probability measures, integrals

and derive efficient parallel algorithms for the computation of MVN distribution functions, including a method based on randomized Korobov and Richtmyer sequences. Timing results of the implementations using the MPI parallel environment are given. 1 Introduction The computation of the multivariate normal

this paper is to constr8z a quasi-rz0AC generrz using (A,#)-SRSs. The following pr2 osition says that if agener823 outputs each element over

The problem of reconstruction of band-limited signals from sampled and noisy observations is studied. It is proposed to sample a signal at quasi-random points, that form a deterministic sequence with properties resembling a random variable being uniformly distributed. Such quasi-random points can

convergence theory, sampling methods and variance reduction techniques. Accelerated convergence for Monte Carlo quadrature is attained using quasi-random (also called low-discrepancy) sequences, which are a deterministic alternative to random or pseudo-random sequences. The points in a quasi-random sequence