Optimal designs for weighted approximation and integration of stochastic processes on \([0,\infty)\)
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Publication:1883588
DOI10.1016/j.jco.2003.10.002zbMath1053.60038OpenAlexW2057229743MaRDI QIDQ1883588
Klaus Ritter, Leszek Plaskota, Grzegorz W. Wasilkowski
Publication date: 13 October 2004
Published in: Journal of Complexity (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jco.2003.10.002
Related Items (9)
Randomly shifted lattice rules for unbounded integrands ⋮ Estimation of number of the derivatives of a Gaussian process ⋮ Optimal algorithms for doubly weighted approximation of univariate functions ⋮ Global smoothness estimation of a Gaussian process from general sequence designs ⋮ Estimating the order of mean-square derivatives with quadratic variations ⋮ Assessing the number of mean square derivatives of a Gaussian process ⋮ Adaptive Itô-Taylor algorithm can optimally approximate the Itô integrals of singular functions ⋮ A Monte Carlo algorithm for weighted integration over $\mathbb {R}^d$ ⋮ Smolyak's algorithm for weighted \(L_1\)-approximation of multivariate functions with bounded \(r\)th mixed derivatives over \(\mathbb R^d\)
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