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Full-Text Articles in Physical Sciences and Mathematics
Canonical Correlation Analysis For Longitudinal Data, Raymond Mccollum
Canonical Correlation Analysis For Longitudinal Data, Raymond Mccollum
Mathematics & Statistics Theses & Dissertations
Data (multivariate data) on two sets of vectors commonly occur in applications. Statistical analysis of these data is usually done using a canonical correlation analysis (CCA). Occurrence of these data at multiple occasions or conditions leads to longitudinal multivariate data for a CCA. We address the problem of canonical correlation analysis on longitudinal data when the data have a Kronecker product covariance structure. Using structured correlation matrices we model the dependency of repeatedly observed data. Recent work of Srivastava, Nahtman, and von Rosen (2008) developed an iterative algorithm to determine the maximum likelihood estimate of the Kronecker product covariance structure …
Canonical Correlation And Correspondence Analysis Of Longitudinal Data, Jayesh Srivastava
Canonical Correlation And Correspondence Analysis Of Longitudinal Data, Jayesh Srivastava
Mathematics & Statistics Theses & Dissertations
Assessing the relationship between two sets of multivariate vectors is an important problem in statistics. Canonical correlation coefficients are used to study these relationships. Canonical correlation analysis (CCA) is a general multivariate method that is mainly used to study relationships when both sets of variables are quantitative. When the variables are qualitative (categorical), a technique called correspondence analysis (CA) is used. Canonical correspondence analysis (CCPA) is used to deal with the case when one set of variables is categorical and the other set is quantitative. By exploiting the interrelationships between these three techniques we first provide a theoretical basis for …