Correspondence Analysis and Data Coding withJavaandR
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Correspondence Analysis and Data Coding With Java and R
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Correspondence analysis has found extensive use in ecology, archaeology, linguistics, and the social sciences as a method for visualizing the patterns of association in a table of frequencies or nonnegative ratio-scale data. Inherent to the method is the expression of the data in each row or each column relative to their respective totals, and it is these sets of relative values (called profile...
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Recent developments of sequencing technologies that allow the production of massive amounts of genomic and genotyping data have highlighted the need for synthetic data representation and pattern recognition methods that can mine and help discovering biologically meaningful knowledge included in such large data sets. Correspondence analysis (CA) is an exploratory descriptive method designed to a...
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Correspondence Analysis (CA) is a statistical method aiming at the graphical representation of the contingencies between the rows and the columns of a categorical data set. A critical step of the CA algorithm is the Singular Value Decomposition (SVD) analysis of a coded matrix. The size of this matrix affects drastically the analysis computational cost. As the size of the matrix increases, the ...
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Correspondence analysis is an explorative computational method for the study of associations between variables. Much like principal component analysis, it displays a low-dimensional projection of the data, e.g., into a plane. It does this, though, for two variables simultaneously, thus revealing associations between them. Here, we demonstrate the applicability of correspondence analysis to and ...
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ژورنال
عنوان ژورنال: Journal of Statistical Software
سال: 2005
ISSN: 1548-7660
DOI: 10.18637/jss.v014.b05