Construction-free median quasi-Monte Carlo rules for function spaces with unspecified smoothness and general weights
@article{Goda2022ConstructionfreeMQ, title={Construction-free median quasi-Monte Carlo rules for function spaces with unspecified smoothness and general weights}, author={Takashi Goda and Pierre L’Ecuyer}, journal={ArXiv}, year={2022}, volume={abs/2201.09413} }
. We study quasi-Monte Carlo (QMC) integration of smooth functions defined over the multi-dimensional unit cube. Inspired by a recent work of Pan and Owen, we study a new construction-free median QMC rule which can exploit the smoothness and the weights of function spaces adaptively. For weighted Korobov spaces, we draw a sample of r independent generating vectors of rank-1 lattice rules, compute the integral estimate for each, and approximate the true integral by the median of these r estimates…
One Citation
Consistency of randomized integration methods
- MathematicsArXiv
- 2022
For integrable functions we provide a weak law of large numbers for structured Monte Carlo methods, such as estimators based on randomized digital nets, Latin hypercube sampling, randomized Frolov…
References
SHOWING 1-10 OF 51 REFERENCES
Obtaining O( N - 2+∈ ) Convergence for Lattice Quadrature Rules
- Mathematics
- 2002
Good lattice quadrature rules are known to have O(N - 2+∈) convergence for periodic integrands with sufficient smoothness. Here it is shown that applying the baker's transformation to lattice rules…
Tent-transformed lattice rules for integration and approximation of multivariate non-periodic functions
- Computer Science, MathematicsJ. Complex.
- 2016
Lattice rules for nonperiodic smooth integrands
- MathematicsNumerische Mathematik
- 2014
This paper studies the embeddings of various reproducing kernel Hilbert spaces and numerical integration in the cosine series function space and shows that by applying the so-called tent transformation to a lattice rule one can achieve the (almost) optimal rate of convergence of the integration error.
Lattice rules in non-periodic subspaces of Sobolev spaces
- MathematicsNumerische Mathematik
- 2019
It is shown that the almost optimal rate of convergence can be achieved for both cases, while a weak dependence of the worst-case error bound on the dimension can be obtained for the former case.
Walsh Spaces Containing Smooth Functions and Quasi-Monte Carlo Rules of Arbitrary High Order
- Mathematics, Computer ScienceSIAM J. Numer. Anal.
- 2008
A Walsh space is defined which contains all functions whose partial mixed derivatives up to order $\delta \ge 1$ exist and have finite variation and it is shown that quasi-Monte Carlo rules based on digital $(t,\alpha,s)$-sequences achieve the optimal rate of convergence of the worst-case error for numerical integration.
Super-polynomial accuracy of one dimensional randomized nets using the median-of-means
- MathematicsArXiv
- 2021
A superpolynomial convergence rate is got for the sample median of 2k − 1 random linearly scrambled estimates, when k = Ω(m) and when f has a p’th derivative that satisfies a λ-Hölder condition.
A Tool for Custom Construction of QMC and RQMC Point Sets
- MathematicsMCQMC
- 2020
We present LatNet Builder, a software tool to find good parameters for lattice rules, polynomial lattice rules, and digital nets in base 2, for quasi-Monte Carlo (QMC) and randomized quasi-Monte…
Digit-by-digit and component-by-component constructions of lattice rules for periodic functions with unknown smoothness
- Computer Science, MathematicsJ. Complex.
- 2021
Stability of lattice rules and polynomial lattice rules constructed by the component-by-component algorithm
- Computer Science, MathematicsJ. Comput. Appl. Math.
- 2021
Recent Advances in Randomized Quasi-Monte Carlo Methods
- Mathematics, Computer Science
- 2002
The main focus is the applicability of quasi-Monte Carlo (QMC) methods to practical problems that involve the estimation of a high-dimensional integral and how this methodology can be coupled with clever transformations of the integrand in order to reduce the variance further.