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Kernel functional canonical correlation analysis

Mirosław Krzyśko et al · Lodz University Press · 2016

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Canonical correlation methods for data representing functions or curves have received much attention in recent years. Such data, known in the literature as functional data (Ramsay and Silverman, 2005), has been the subject of much recent research interest. Examples of functional data can be found in several application domains, such as medicine, economics, meteorology and many others. Unfortunately, the multivariate data canonical correlation methods cannot be used directly for functional data, because of the problem of dimensionality and difficulty in taking into account the correlation and order of functional data. The problem of constructing canonical correlations and canonical variables for functional data was addressed by Leurgans et al. (1993), and further developments were made by Ramsay and Silverman (2005). In this paper we propose a new method of constructing canonical correlations and canonical variables for functional data.

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APA 7

al, M. K. E. (2016). Kernel functional canonical correlation analysis. https://doi.org/10.18778/0208-6018.325.12

MLA

al, Mirosław Krzyśko et. "Kernel functional canonical correlation analysis." 2016. https://doi.org/10.18778/0208-6018.325.12.

Chicago

al, Mirosław Krzyśko et. 2016. "Kernel functional canonical correlation analysis.". https://doi.org/10.18778/0208-6018.325.12.

Harvard

al, M. K. E. 2016, Kernel functional canonical correlation analysis, Lodz University Press, available at: https://doi.org/10.18778/0208-6018.325.12 [Accessed 8 Aug. 2026].

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Title
Kernel functional canonical correlation analysis
Author / contributors
Mirosław Krzyśko et al
Publisher
Lodz University Press
Publication year
2016
ISSN
0208-6018
ISSN
0208-6018
Language
English

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