Biometrical Letters

ISSN:1896-3811

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Volume (57) Number 1 pp. 1-12

Tomasz Górecki 1, Mirosław Krzyśko 2, Waldemar Wołyński 1

1Faculty of Mathematics and Computer Science, Adam Mickiewicz University, Uniwersytetu Poznańskiego 4, 61-614, Poznań, Poland
2Interfaculty Institute of Mathematics and Statistics, The President Stanisław Wojciechowski State University of Applied Sciences in Kalisz, 62-800, Kalisz, Poland

Generalized canonical correlation analysis for functional data

Summary

There is a growing need to analyze data sets characterized by several sets of variables observed on the same set of individuals. Such complex data structures are known as multiblock (or multiple-set) data sets. Multi-block data sets are encountered in diverse fields including bioinformatics, chemometrics, food analysis, etc. Generalized Canonical Correlation Analysis (GCCA) is a very powerful method to study this kind of relationships between blocks. It can also be viewed as a method for the integration of information from K > 2 distinct sources (Takane and Oshima-Takane 2002). In this paper, GCCA is considered in the context of multivariate functional data. Such data are treated as realizations of multivariate random processes. GCCA is a technique that allows the joint analysis of several sets of data through dimensionality reduction. The central problem of GCCA is to construct a series of components aiming to maximize the association among the multiple variable sets. This method will be presented for multivariate functional data. Finally, a practical example will be discussed.

Keywords: multivariate functional data, generalized canonical correlation analysis

DOI: 10.2478/bile-2020-0001

For citation:

MLA Górecki, Tomasz, et al. "Generalized canonical correlation analysis for functional data." Biometrical Letters 57.1 (2020): 1-12. DOI: 10.2478/bile-2020-0001
APA Górecki, T., Krzyśko, M., & Wołyński, W. (2020). Generalized canonical correlation analysis for functional data. Biometrical Letters 57(1), 1-12 DOI: 10.2478/bile-2020-0001
ISO 690 GóRECKI, Tomasz, KRZYśKO, Mirosław, WOłYńSKI, Waldemar. Generalized canonical correlation analysis for functional data. Biometrical Letters, 2020, 57.1: 1-12. DOI: 10.2478/bile-2020-0001
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