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  • Search: subject:"Reproducing kernel Hilbert spaces"
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Year of publication
Subject
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ANOVA decomposition 1 Canonical correlation analysis 1 Frames 1 Functional data analysis 1 Linear mixed-effects model 1 Longitudinal data 1 Overcomplete atomic dictionaries 1 Reproducing Kernel Hilbert spaces 1 Reproducing kernel Hilbert spaces 1 Sparse approximation 1 Wavelets 1 multilevel algorithms 1 numerical integration 1 randomized algorithms 1 reproducing kernel Hilbert spaces 1 scrambled polynomial lattice rules 1
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Online availability
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Undetermined 2 Free 1
Type of publication
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Article 2 Book / Working Paper 1
Language
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Undetermined 3
Author
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Baldeaux, Jan 1 Capobianco, Enrico 1 Gnewuch, Michael 1 Lee, Seokho 1 Shin, Hyejin 1
Institution
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Finance Discipline Group, Business School 1
Published in...
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Journal of Multivariate Analysis 1 Physica A: Statistical Mechanics and its Applications 1 Research Paper Series / Finance Discipline Group, Business School 1
Source
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RePEc 3
Showing 1 - 3 of 3
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Optimal Randomized Multilevel Algorithms for Infinite-Dimensional Integration on Function Spaces with ANOVA-Type Decomposition
Gnewuch, Michael; Baldeaux, Jan - Finance Discipline Group, Business School - 2012
In this paper, we consider the infinite-dimensional integration problem on weighted reproducing kernel Hilbert spaces …
Persistent link: https://www.econbiz.de/10010883497
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Canonical correlation analysis for irregularly and sparsely observed functional data
Shin, Hyejin; Lee, Seokho - In: Journal of Multivariate Analysis 134 (2015) C, pp. 1-18
Several approaches for functional canonical correlation analysis have been developed to measure the association between paired functional data. However, the existing methods in the literature have been developed for dense and balanced functional data, and they cannot be directly applicable to...
Persistent link: https://www.econbiz.de/10011189575
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Kernel methods and flexible inference for complex stochastic dynamics
Capobianco, Enrico - In: Physica A: Statistical Mechanics and its Applications 387 (2008) 16, pp. 4077-4098
Approximation theory suggests that series expansions and projections represent standard tools for random process applications from both numerical and statistical standpoints. Such instruments emphasize the role of both sparsity and smoothness for compression purposes, the decorrelation power...
Persistent link: https://www.econbiz.de/10010873605
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