Accelerating the Convergence of Lattice Methods by Importance Sampling-Based Transformations

DOI10.1007/978-3-642-27440-4_32zbMath1271.65046OpenAlexW2187413072MaRDI QIDQ5326131

Jerome Spanier, Earl H. Maize, John Sepikas

Publication date: 31 July 2013

Published in: Springer Proceedings in Mathematics & Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-642-27440-4_32

zbMATH Keywords

convergenceimportance samplingnumerical examplesintegral equationsquadrature formulas

Mathematics Subject Classification ID

Monte Carlo methods (65C05) Multidimensional problems (41A63) Approximate quadratures (41A55) Numerical quadrature and cubature formulas (65D32)

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Cites Work

• Point sets and sequences with small discrepancy
• Construction algorithms for good extensible lattice rules
• The existence of good extensible rank-1 lattices
• Multidimensional quadrature algorithms at higher degree and/or dimension
• A New Family of Estimators for Random Walk Problems
• Quasi-Random Methods for Estimating Integrals Using Relatively Small Samples
• Extensible Lattice Sequences for Quasi-Monte Carlo Quadrature
• Fast convergence of quasi-Monte Carlo for a class of isotropic integrals
• Weighted Uniform Sampling — a Monte Carlo Technique for Reducing Variance
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