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Author : R. A. H. Price
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (643 download)
Download or read book Discarding Variables Using Canonical Correlation Analysis written by R. A. H. Price and published by . This book was released on 1977 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Bruce Thompson
Publisher : SAGE
ISBN 13 : 9780803923928
Total Pages : 76 pages
Book Rating : 4.9/5 (239 download)
Download or read book Canonical Correlation Analysis written by Bruce Thompson and published by SAGE. This book was released on 1984-11 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent advances both in statistical methodology and in computer automation are making canonical correlation analysis available to more and more researchers. In an essentially nonmathematical presentation that provides numerous examples, this volume explains the basic features of this sophisticated technique. Learn more about "The Little Green Book" - QASS Series! Click Here
Author : Mark S. Levine
Publisher : SAGE
ISBN 13 : 9780803906556
Total Pages : 68 pages
Book Rating : 4.9/5 (65 download)
Download or read book Canonical Analysis and Factor Comparison written by Mark S. Levine and published by SAGE. This book was released on 1977-04 with total page 68 pages. Available in PDF, EPUB and Kindle. Book excerpt: Canonical correlational analysis; Factor comparison techniques; References.
Author : Sudhanshu K. Mishra
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (137 download)
Download or read book Representation-Constrained Canonical Correlation Analysis written by Sudhanshu K. Mishra and published by . This book was released on 2009 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The classical canonical correlation analysis is extremely greedy to maximize the squared correlation between two sets of variables. As a result, if one of the variables in the dataset-1 is very highly correlated with another variable in the dataset-2, the canonical correlation will be very high irrespective of the correlation among the rest of the variables in the two datasets. We intend here to propose an alternative measure of association between two sets of variables that will not permit the greed of a select few variables in the datasets to prevail upon the fellow variables so much as to deprive the latter of contributing to their representative variables or canonical variates. Our proposed Representation-Constrained Canonical correlation (RCCCA) Analysis has the Classical Canonical Correlation Analysis (CCCA) at its one end (lambda=0) and the Classical Principal Component Analysis (CPCA) at the other (as lambda tends to be very large). In between it gives us a compromise solution. By a proper choice of lambda, one can avoid hijacking of the representation issue of two datasets by a lone couple of highly correlated variables across those datasets. This advantage of the RCCCA over the CCCA deserves a serious attention by the researchers using statistical tools for data analysis.
Author : Eeke van der Burg
Publisher :
ISBN 13 :
Total Pages : 256 pages
Book Rating : 4.F/5 ( download)
Download or read book Nonlinear Canonical Correlation and Some Related Techniques written by Eeke van der Burg and published by . This book was released on 1988 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Jayesh Srivastava
Publisher :
ISBN 13 : 9780549069508
Total Pages : 99 pages
Book Rating : 4.0/5 (695 download)
Download or read book Canonical Correlation and Correspondence Analysis of Longitudinal Data written by Jayesh Srivastava and published by . This book was released on 2007 with total page 99 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 CCPA.
Author : Johny K. Johansson
Publisher :
ISBN 13 :
Total Pages : 84 pages
Book Rating : 4.:/5 (31 download)
Download or read book Canonical Correlation, Multiple Regression and Simultaneous Systems written by Johny K. Johansson and published by . This book was released on 1974 with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Eeke van der Burg
Publisher :
ISBN 13 :
Total Pages : 28 pages
Book Rating : 4.:/5 (649 download)
Download or read book Nonlinear Canonical Correlation Analysis with K Sets of Variables written by Eeke van der Burg and published by . This book was released on 1987 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Noriah Mohammed Al-Kandari
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (646 download)
Download or read book Variable Selection and Interpretation in Canonical Correlation Analysis written by Noriah Mohammed Al-Kandari and published by . This book was released on 1994 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Franklin D. Wilson
Publisher :
ISBN 13 :
Total Pages : 46 pages
Book Rating : 4.3/5 (91 download)
Download or read book Canonical Correlation and the Relations Between Sets of Variables written by Franklin D. Wilson and published by . This book was released on 1975 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Peter Boedeker
Publisher :
ISBN 13 : 9781526421036
Total Pages : 0 pages
Book Rating : 4.4/5 (21 download)
Download or read book Canonical Correlation Analysis written by Peter Boedeker and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Canonical correlation analysis (CCA) is a multivariate statistical technique that can be used in research scenarios in which there are several correlated outcomes of interest. Instead of separating analyses of these outcomes into several univariate analyses, a single application of CCA can capture the relationship across variables while honoring the fact that variables are correlated within sets. In CCA, the variability shared between two variable sets is partitioned into independent relationships and these relationships are characterized by the variables that contribute most in their formation. CCA is described here in detail, connecting the multivariate procedure to simple bivariate correlation and multiple regression and highlighting its position in the general linear model. After reviewing the procedure and important terminology, an accessible example is provided. The example is reproducible with data and syntax available online.
Author : Thompson
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (82 download)
Download or read book Canonical Correlation Analysis written by Thompson and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Y. Fujikoshi
Publisher :
ISBN 13 :
Total Pages : 20 pages
Book Rating : 4.:/5 (227 download)
Download or read book Effect of Additional Variables in Principal Component Analysis, Discriminant Analysis and Canonical Correlation Analysis written by Y. Fujikoshi and published by . This book was released on 1985 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, the authors derived asmptotic distributions of changes in certain functions of the eigenvalues of the sample covariance matrix, MANOVA matrix and canonical correlation matrix when some variables are added to the original sets of variables. The above results are useful in finding out as to whether the new variables give additional information for statistical inference; multivariate analysis; Wishart distribution. (Author).
Author : Bastiaan Tom Rijken van Olst
Publisher :
ISBN 13 :
Total Pages : 156 pages
Book Rating : 4.:/5 (27 download)
Download or read book Canonical Correlation and Canonical Variables in Econometrics written by Bastiaan Tom Rijken van Olst and published by . This book was released on 1981 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Ines Wilms
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (931 download)
Download or read book Sparse Canonical Correlation Analysis from a Predictive Point of View written by Ines Wilms and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Ines Wilms
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (931 download)
Download or read book Robust Sparse Canonical Correlation Analysis written by Ines Wilms and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Ying Xu
Publisher :
ISBN 13 :
Total Pages : 66 pages
Book Rating : 4.:/5 (94 download)
Download or read book Regularization Methods for Canonical Correlation Analysis, Rank Correlation Matrices and Renyi Correlation Matrices written by Ying Xu and published by . This book was released on 2011 with total page 66 pages. Available in PDF, EPUB and Kindle. Book excerpt: In multivariate analysis, canonical correlation analysis is a method that enable us to gain insight into the relationships between the two sets of variables. It determines linear combinations of variables of each type with maximal correlation between the two linear combinations. However, in high dimensional data analysis, insufficient sample size may lead to computational problems, inconsistent estimates of parameters. In Chapter 1, three new methods of regularization are presented to improve the traditional CCA estimator in high dimensional settings. Theoretical results have been derived and the methods are evaluated using simulated data. While the linear methods are successful in many circumstances, it certainly has some limitations, especially in cases where strong nonlinear dependencies exist. In Chapter 2, I investigate some other measures of dependence, including the rank correlation and its extensions, which can capture some non-linear relationship between variables. Finally the Renyi correlation is considered in Chapter 3. I also complement my analysis with simulations that demonstrate the theoretical results.
