Scrambled polynomial lattice rules for infinite-dimensional integration

In the random case setting, scrambled polynomial lattice rules, as discussed in Baldeaux and Dick (Numer. Math. 119:271–297, 2011), enjoy more favorable strong tractability properties than scrambled digital nets. This short note discusses the application of scrambled polynomial lattice rules to infinite-dimensional integration. In Hickernell et al. (J Complex 26:229–254, 2010), infinite-dimensional integration in the random case setting was examined in detail, and results based on scrambled digital nets were presented. Exploiting these improved strong tractability properties of scrambled polynomial lattice rules and making use of the analysis presented in Hickernell et al. (J Complex 26:229–254, 2010), we improve on the results that were achieved using scrambled digital nets.

[1]  Stefan Heinrich,et al.  Multilevel Monte Carlo Methods , 2001, LSSC.

[2]  Fred J. Hickernell,et al.  Deterministic multi-level algorithms for infinite-dimensional integration on RN , 2011, J. Complex..

[3]  Klaus Ritter,et al.  Average-case analysis of numerical problems , 2000, Lecture notes in mathematics.

[4]  E. Novak Deterministic and Stochastic Error Bounds in Numerical Analysis , 1988 .

[5]  Fred J. Hickernell,et al.  Multi-level Monte Carlo algorithms for infinite-dimensional integration on RN , 2010, J. Complex..

[6]  Michael Gnewuch,et al.  Infinite-dimensional integration on weighted Hilbert spaces , 2012, Math. Comput..

[7]  Grzegorz W. Wasilkowski,et al.  Tractability of infinite-dimensional integration in the worst case and randomized settings , 2011, J. Complex..

[8]  Stefan Heinrich,et al.  Monte Carlo Complexity of Global Solution of Integral Equations , 1998, J. Complex..

[9]  K. Ritter,et al.  Multi-Level {M}onte {C}arlo Algorithms for Infinite-Dimensional Integration on $\mathbb{R}^\mathbb{N}$ , 2010 .

[10]  A. Owen Randomly Permuted (t,m,s)-Nets and (t, s)-Sequences , 1995 .

[11]  Josef Dick,et al.  A construction of polynomial lattice rules with small gain coefficients , 2011, Numerische Mathematik.

[12]  Fred J. Hickernell,et al.  Strong tractability of integration using scrambled Niederreiter points , 2005, Math. Comput..

[13]  Junichi Imai,et al.  Quasi-Monte Carlo Method for Infinitely Divisible Random Vectors via Series Representations , 2010, SIAM J. Sci. Comput..

[14]  Fred J. Hickernell,et al.  Monte Carlo Simulation of Stochastic Integrals when the Cost of Function Evaluation Is Dimension Dependent , 2009 .

[15]  Steffen Dereich,et al.  Infinite-Dimensional Quadrature and Approximation of Distributions , 2009, Found. Comput. Math..

[16]  M. Giles Improved Multilevel Monte Carlo Convergence using the Milstein Scheme , 2008 .

[17]  Michael B. Giles,et al.  Multilevel Monte Carlo Path Simulation , 2008, Oper. Res..

[18]  H. Woxniakowski Information-Based Complexity , 1988 .

[19]  Ben Niu,et al.  Deterministic Multi-level Algorithms for Infinite-dimensional Integration on {$\mathbb{R}^{\mathbb{N}}$} , 2010 .

[20]  Henryk Wozniakowski,et al.  Liberating the dimension , 2010, J. Complex..

[21]  Michael Gnewuch,et al.  Weighted geometric discrepancies and numerical integration on reproducing kernel Hilbert spaces , 2012, J. Complex..