Sep 8, 2023 · We show how to use these properties to get a non-asymptotic and computable upper bound for the integral of f over [0,1]^d.
We show how to use these properties to get a non-asymptotic and computable upper bound for the integral of f over [ 0 , 1 ] d.
Sep 8, 2023 · An analogous non-positive local discrepancy (NPLD) property provides a computable lower bound. It has been known since Gabai (1967) that the two ...
Aug 31, 2024 · We show how to use these properties to get a non-asymptotic and computable upper bound for the integral of $f$ over $[0,1]^{d}$.
Apr 1, 2024 · These methods require special QMC points that have a non-negative local discrepancy property along with an integrand that has a complete ...
One of the main challenges when studying QMC rules is to find reliable error bounds. In this talk, we present a way of finding a non-asymptotic and computable ...
Volume 13 Issue 3 | Information and Inference: A Journal of the IMA
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Computable error bounds for quasi-Monte Carlo using points with non-negative local discrepancy. Michael Gnewuch and others. Information and Inference: A ...
Owen, Z. Pan. Computable error bounds for quasi-Monte Carlo using points with non-negative local discrepancy. Information and Inference 13, iaae021, 2024. D ...
Computable error bounds for quasi-Monte Carlo using points with non-negative local discrepancy. 2024, Information and Inference. On the Distribution of ...
2023. M. Gnewuch, P. Kritzer, A. B. Owen and Z. Pan Computable error bounds for quasi-Monte Carlo using points with non-negative local discrepancy (coming soon ...