Abstract Details
Activity Number:
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403
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Type:
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Contributed
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Date/Time:
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Tuesday, August 5, 2014 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistics in Marketing
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Abstract #311929
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View Presentation
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Title:
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GPCIV and GraphPCA: Two R Packages for PCA of Complex Data
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Author(s):
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Brahim Brahim and Sun Makosso-Kallyth*+
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Companies:
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Big Data Visualizations and McMaster University
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Keywords:
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PCA ;
Big Data ;
R Package ;
Data Visualization ;
Data Analysis
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Abstract:
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We present two R packages for the achievement of Principal Component Analysis PCA of complex data (interval, histogram). The first one GPCSIV-package {GPCSIV} implements an extension of principal component analysis (PCA) tailored to handle multiple data tables. These multiple data tables contain the same number of Interval variables and the same observations. The second one, GraphPCA-package {GraphPCA}, implements a histogram principal components analysis. These packages provides numerical and graphical tools and can handle Big Data in the sense that the variation in massive data can be described by intervals [a, b], histogram and multiple tables.
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