Abstract
Matsumoto, Saito and Matoba recently proposed the Walsh figure of merit (WAFOM), which is a computable criterion for quasi-Monte Carlo point sets using digital nets. Several algorithms have been proposed for finding low-WAFOM point sets. In the existing algorithms, the number of points is fixed in advance, but extensible point sets are preferred in some applications. In this paper, we propose a random search algorithm for extensible low-WAFOM point sets. For this, we introduce a method that uses lookup tables to compute WAFOM faster. Numerical results show that our extensible low-WAFOM point sets are comparable with Niederreiter–Xing sequences for some low-dimensional and smooth test functions.
Funding source: Japan Society for the Promotion of Science
Award Identifier / Grant number: 26730015
Award Identifier / Grant number: 24.7985
Award Identifier / Grant number: 26310211
Award Identifier / Grant number: 15K13460
Funding statement: The author was partially supported by the Grants-in-Aid for Young Scientists (B) #26730015, for JSPS Fellows 247985, for Scientific Research (B) 26310211, and for Challenging Exploratory Research #15K13460 from the Japan Society for the Promotion of Scientific Research.
Acknowledgements
In an earlier version of this paper, Mr. Ryuichi Ohori checked the code in C written by the author, in particular for the correctness of the WAFOM values in Section 3, and gave the author invaluable comments to improve the presentation. The author thanks him for his help.
References
[1] Barthelmann V., Novak E. and Ritter K., High dimensional polynomial interpolation on sparse grids, Adv. Comput. Math. 12 (2000), 273–288. 10.1023/A:1018977404843Suche in Google Scholar
[2] Bratley P., Fox B. L. and Niederreiter H., Implementation and tests of low-discrepancy sequences, ACM Trans. Model. Comput. Simul. 2 (1992), 195–213. 10.1145/146382.146385Suche in Google Scholar
[3] Dick J., Explicit constructions of quasi-Monte Carlo rules for the numerical integration of high-dimensional periodic functions, SIAM J. Numer. Anal. 45 (2007), 2141–2176. 10.1137/060658916Suche in Google Scholar
[4] Dick J., Walsh spaces containing smooth functions and quasi-Monte Carlo rules of arbitrary high order, SIAM J. Numer. Anal. 46 (2008), 1519–1553. 10.1137/060666639Suche in Google Scholar
[5] Dick J., On quasi-Monte Carlo rules achieving higher order convergence, Monte Carlo and Quasi-Monte Carlo Methods 2008 (Montréal 2009), Springer, Berlin (2009), 73–96. 10.1007/978-3-642-04107-5_5Suche in Google Scholar
[6] Dick J. and Matsumoto M., On the fast computation of the weight enumerator polynomial and the t value of digital nets over finite abelian groups, SIAM J. Discrete Math. 27 (2013), 1335–1359. 10.1137/120893677Suche in Google Scholar
[7] Dick J. and Pillichshammer F., Digital Nets and Sequences. Discrepancy Theory and Quasi-Monte Carlo Integration, Cambridge University Press, Cambridge, 2010. 10.1017/CBO9780511761188Suche in Google Scholar
[8] Genz A., Testing multidimensional integration routines, Tools, Methods, and Languages for Scientific and Engineering Computation, North-Holland, Amsterdam (1984), 81–94. Suche in Google Scholar
[9] Genz A., A package for testing multiple integration subroutines, Numerical Integration: Recent Developments, Software and Applications, Springer, Berlin (1987), 337–340. 10.1007/978-94-009-3889-2_33Suche in Google Scholar
[10] Goda T., Ohori R., Suzuki K. and Yoshiki T., The mean square quasi-Monte Carlo error for digitally shifted digital nets, Monte Carlo and Quasi-Monte Carlo Methods, Springer Proc. Math. Stat. 163, Springer, Berlin (2016), 331–350. 10.1007/978-3-319-33507-0_16Suche in Google Scholar
[11] Harase S., Quasi-Monte Carlo point sets with small t-values and WAFOM, Appl. Math. Comput. 254 (2015), 318–326. 10.1016/j.amc.2014.12.144Suche in Google Scholar
[12] Hellekalek P. and Leeb H., Dyadic diaphony, Acta Arith. 80 (1997), 187–196. 10.4064/aa-80-2-187-196Suche in Google Scholar
[13] Joe S. and Kuo F. Y., Constructing Sobol’ sequences with better two-dimensional projections, SIAM J. Sci. Comput. 30 (2008), 2635–2654. 10.1137/070709359Suche in Google Scholar
[14]
Matoušek J.,
On the
[15] Matsumoto M. and Ohori R., Walsh figure of merit for digital nets: An easy measure for higher order convergent QMC, Monte Carlo and Quasi-Monte Carlo Methods, Springer Proc. Math. Stat. 163, Springer, Berlin (2016), 143–160. 10.1007/978-3-319-33507-0_5Suche in Google Scholar
[16] Matsumoto M., Saito M. and Matoba K., A computable figure of merit for quasi-Monte Carlo point sets, Math. Comp. 83 (2014), 1233–1250. 10.1090/S0025-5718-2013-02774-3Suche in Google Scholar
[17] Matsumoto M. and Yoshiki T., Existence of higher order convergent quasi-Monte Carlo rules via Walsh figure of merit, Monte Carlo and Quasi-Monte Carlo Methods 2012, Springer Proc. Math. Stat. 65, Springer, Berlin (2013), 569–579. 10.1007/978-3-642-41095-6_29Suche in Google Scholar
[18] Niederreiter H., Point sets and sequences with small discrepancy, Monatsh. Math. 104 (1987), 273–337. 10.1007/BF01294651Suche in Google Scholar
[19] Niederreiter H., Random Number Generation and Quasi-Monte Carlo Methods, CBMS-NSF Regional Conf. Ser. in Appl. Math. 63, Society for Industrial and Applied Mathematics (SIAM), Philadelphia, 1992. 10.1137/1.9781611970081Suche in Google Scholar
[20] Novak E. and Ritter K., High-dimensional integration of smooth functions over cubes, Numer. Math. 75 (1996), 79–97. 10.1007/s002110050231Suche in Google Scholar
[21] Ohori R., E,fficient quasi-Monte Carlo integration by adjusting the derivation-sensitivity parameter of Walsh figure of merit Master’s thesis, Graduate School of Mathematical Sciences, The University of Tokyo, Tokyo, 2015. Suche in Google Scholar
[22] Ohori R. and Yoshiki T., Walsh figure of merit is efficiently approximable, in preparation. Suche in Google Scholar
[23] Owen A. B., The dimension distribution and quadrature test functions, Statist. Sinica 13 (2003), 1–17. Suche in Google Scholar
[24] Patterson D. A. and Hennessy J. L., Computer Organization and Design, Fifth Edition: The Hardware/Software Interface, 5th ed., Morgan Kaufmann Publishers, San Francisco, 2013. Suche in Google Scholar
[25] Pirsic G., A software implementation of Niederreiter–Xing sequences, Monte Carlo and Quasi-Monte Carlo Methods 2000 (Hong Kong 2000), Springer, Berlin (2002), 434–445. 10.1007/978-3-642-56046-0_30Suche in Google Scholar
[26] Pirsic G. and Schmid W. C., Calculation of the quality parameter of digital nets and application to their construction, J. Complexity 17 (2001), 827–839. 10.1006/jcom.2001.0597Suche in Google Scholar
[27] Sloan I. H. and Joe S., Lattice Methods for Multiple Integration, Clarendon Press, New York, 1994. 10.1093/oso/9780198534723.001.0001Suche in Google Scholar
[28] Sobol’ I. M., Distribution of points in a cube and approximate evaluation of integrals, Z̆. Vyčisl. Mat. i Mat. Fiz. 7 (1967), 784–802. 10.1016/0041-5553(67)90144-9Suche in Google Scholar
[29] Suzuki K., An explicit construction of point sets with large minimum Dick weight, J. Complexity 30 (2014), 347–354. 10.1016/j.jco.2013.12.002Suche in Google Scholar
[30] Suzuki K., WAFOM over abelian groups for quasi-Monte Carlo point sets, Hiroshima Math. J. 45 (2015), 341–364. 10.32917/hmj/1448323769Suche in Google Scholar
[31] Suzuki K., Super-polynomial convergence and tractability of multivariate integration for infinitely times differentiable functions, J. Complexity (2016), 10.1016/j.jco.2016.10.002. 10.1016/j.jco.2016.10.002Suche in Google Scholar
[32] Xing C. P. and Niederreiter H., A construction of low-discrepancy sequences using global function fields, Acta Arith. 73 (1995), 87–102. 10.4064/aa-73-1-87-102Suche in Google Scholar
[33] Yoshiki T., A lower bound on WAFOM, Hiroshima Math. J. 44 (2014), 261–266. 10.32917/hmj/1419619746Suche in Google Scholar
[34] Yoshiki T., Bounds on Walsh coefficients by dyadic difference and a new Koksma–Hlawka type inequality for quasi-Monte Carlo integration, preprint 2015, https://arxiv.org/abs/1504.03175. 10.32917/hmj/1499392824Suche in Google Scholar
© 2016 by De Gruyter
Artikel in diesem Heft
- Frontmatter
- Random walk on spheres method for solving drift-diffusion problems
- On the construction of boundary preserving numerical schemes
- Perfect and ε-perfect simulation methods for the one-dimensional Kac equation
- Approximation of Euler–Maruyama for one-dimensional stochastic differential equations involving the local times of the unknown process
- Improved Markov Chain Monte Carlo method for cryptanalysis substitution-transposition cipher
- The planar Couette flow with slip and jump boundary conditions in a microchannel
- A search for extensible low-WAFOM point sets
Artikel in diesem Heft
- Frontmatter
- Random walk on spheres method for solving drift-diffusion problems
- On the construction of boundary preserving numerical schemes
- Perfect and ε-perfect simulation methods for the one-dimensional Kac equation
- Approximation of Euler–Maruyama for one-dimensional stochastic differential equations involving the local times of the unknown process
- Improved Markov Chain Monte Carlo method for cryptanalysis substitution-transposition cipher
- The planar Couette flow with slip and jump boundary conditions in a microchannel
- A search for extensible low-WAFOM point sets