On the use of low discrepancy sequences in Monte Carlo methods

[1]  Gilles Pagès,et al.  Sequences with low discrepancy and pseudo-random numbers:theoretical results and numerical tests , 1997 .

[2]  N. Bouleau,et al.  Numerical methods for stochastic processes , 1993 .

[3]  William H. Press,et al.  The Art of Scientific Computing Second Edition , 1998 .

[4]  H. Faure.  Good permutations for extreme discrepancy , 1992 .

[5]  Harald Niederreiter,et al.  Random number generation and Quasi-Monte Carlo methods , 1992, CBMS-NSF regional conference series in applied mathematics.

[6]  J. E. H. Shaw,et al.  A Quasirandom Approach to Integration in Bayesian Statistics , 1988 .

[7]  Paul Bratley,et al.  Algorithm 659: Implementing Sobol's quasirandom sequence generator , 1988, TOMS.

[8]  J. Beck,et al.  Irregularities of distribution , 1987 .

[9]  P. K. Sarkar,et al.  A comparative study of Pseudo and Quasi random sequences for the solution intergral equations , 1987 .

[10]  Bennett L. Fox,et al.  Algorithm 647: Implementation and Relative Efficiency of Quasirandom Sequence Generators , 1986, TOMS.

[11]  H. Keng,et al.  Applications of number theory to numerical analysis , 1981 .

[12]  E. Braaten,et al.  An Improved Low-Discrepancy Sequence for Multidimensional Quasi-Monte Carlo Integration , 1979 .

[13]  H. Niederreiter.  Quasi-Monte Carlo methods and pseudo-random numbers , 1978 .

[14]  R. Cranley,et al.  Randomization of Number Theoretic Methods for Multiple Integration , 1976 .

[15]  I. Sobol.  Uniformly distributed sequences with an additional uniform property , 1976 .

[16]  I. Sobol.  On the distribution of points in a cube and the approximate evaluation of integrals , 1967 .