Random number generation and quasi-Monte Carlo methods
Random number generation and quasi-Monte Carlo methods
Error bounds for the integration of singular functions using equidistributed sequences
Journal of Complexity
Shifted lattice rules based on a general weighted discrepancy for integrals over Euclidean space
Journal of Computational and Applied Mathematics
On the convergence of quasi-random sampling/importance resampling
Mathematics and Computers in Simulation
Computing Expectation Values for Molecular Quantum Dynamics
SIAM Journal on Scientific Computing
Using box-muller with low discrepancy points
ICCSA'06 Proceedings of the 2006 international conference on Computational Science and Its Applications - Volume Part V
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In this article we investigate quasi-Monte Carlo (QMC) methods for multidimensional improper integrals with respect to a measure other than the uniform distribution. Additionally, the integrand is allowed to be unbounded at the lower boundary of the integration domain. We establish convergence of the QMC estimator to the value of the improper integral under conditions involving both the integrand and the sequence used. Furthermore, we suggest a modification of an approach proposed by Hlawka and Mück for the creation of low-discrepancy sequences with regard to a given density, which are suited for singular integrands.