Abstract
This paper has several folds. We make first new permutation choices in Halton sequences to improve their distributions. These choices are multi-dimensional and they are made for two different discrepancies. We show that multi-dimensional choices are better for standard quasi-Monte Carlo methods. We also use these sequences as a variance reduction technique in Monte Carlo methods, which greatly improves the convergence accuracy of the estimators. For this kind of use, we observe that one-dimensional choices are more efficient.
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Tuffin, B. (1998). A new permutation choice in Halton sequences. In: Niederreiter, H., Hellekalek, P., Larcher, G., Zinterhof, P. (eds) Monte Carlo and Quasi-Monte Carlo Methods 1996. Lecture Notes in Statistics, vol 127. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-1690-2_30
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DOI: https://doi.org/10.1007/978-1-4612-1690-2_30
Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-98335-6
Online ISBN: 978-1-4612-1690-2
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