Results 271 to 280 of about 496,805 (322)

Residual Canonical Correlations

Canadian Mathematical Bulletin, 1985
AbstractResidual canonical correlations are defined and are derived in terms of canonical correlations. Some measures of residual association are also defined, in terms of the residual canonical correlations and some possible applications are suggested.
Kshirsagar, Anant M., Gupta, R. P.
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Constrained Canonical Correlation

Psychometrika, 1982
This paper explores some of the problems associated with traditional canonical correlation. A response surface methodology is developed to examine the stability of the derived linear functions, where one wishes to investigate how much the coefficients can change and still be in an ɛ-neighborhood of the globally optimum canonical correlation value.
DeSarbo, Wayne S., Hausman, Robert E., Lin, Shen, Thompson, Wesley   +3 more
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Canonical correlations and canonical time series

1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings, 2002
In this paper, we revisit the problem of interrelations between large correlated data sets by considering cross correlations between a few linear combinations of the elements of each. This problem was studied by Hotelling (see Biometrika, vol.28, p.321-77) and Anderson (1958).
J.K. Thomas, L.L. Scharf
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Canonical Correlation Analysis

2012
Canonical correlation analysis (CCA) is one of the most important tools of multivariate statistical analysis. Its extension to the functional context is not trivial, and in many ways illustrates the differences between multivariate and functional data. One of the most influential contributions has been made by Leurgans et al.
Lajos Horváth, Piotr Kokoszka
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Canonical Correlation Analysis

2003
Complex multivariate data structures are better understood by studying low-dimensional projections. For a joint study of two data sets, we may ask what type of low-dimensional projection helps in finding possible joint structures for the two samples.
Wolfgang Karl Härdle, Léopold Simar
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Canonical correlations and canonical variates

1985
In this chapter we shall summarize the essential elements of the theory of canonical correlations and variates. We shall begin by formulating the problem. The derivation of canonical correlations and canonical variates will then be taken up. Canonical analysis can be derived in several ways.
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Canonical Correlation Analysis

2019
In many applications, one wants to associate one kind of data with another. For example, every data item could be a video sequence together with its sound track. You might want to use this data to learn to associate sounds with video, so you can predict a sound for a new, silent, video.
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Integrative oncology: Addressing the global challenges of cancer prevention and treatment

Ca-A Cancer Journal for Clinicians, 2022
Jun J Mao,, Msce, Lorenzo Cohen, Karen M Mustian   +2 more
exaly  

Canonical Correlation Analysis

2017
This chapter covers classical and robust canonical correlation analysis (CCA). Let \(\varvec{x}\) be the \(p \times 1\) vector of predictors, and partition \({\varvec{x}} = ({\varvec{w}}^T, {\varvec{y}}^T)^T\) where \({\varvec{w}}\) is \(m \times 1\) and \({\varvec{y}}\) is \(q \times 1\) with \(m = p-q \le q\) and \(m, q \ge 1\). If \(m = 1\) and \(q =
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Canonical correlation

2014
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