Correspondence analysis of raw data
AbstractCorrespondence analysis has found extensive use in ecology, archeology, 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 profiles) that are visualized. This ‘relativization’ of the data makes perfect sense when the margins of the table represent samples from sub-populations of inherently different sizes. But in some ecological applications sampling is performed on equal areas or equal volumes so that the absolute levels of the observed occurrences may be of relevance, in which case relativization may not be required. In this paper we define the correspondence analysis of the raw ‘unrelativized’ data and discuss its properties, comparing this new method to regular correspondence analysis and to a related variant of non-symmetric correspondence analysis.
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Bibliographic InfoPaper provided by Department of Economics and Business, Universitat Pompeu Fabra in its series Economics Working Papers with number 1112.
Date of creation: Sep 2008
Date of revision: Jul 2009
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Web page: http://www.econ.upf.edu/
Abundance data; biplot; Bray-Curtis dissimilarity; profile; size and shape; visualisation;
Find related papers by JEL classification:
- C19 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Other
- C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software
This paper has been announced in the following NEP Reports:
- NEP-ALL-2008-10-13 (All new papers)
- NEP-ECM-2008-10-13 (Econometrics)
- NEP-ENV-2008-10-13 (Environmental Economics)
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- Oleg Nenadic & Michael Greenacre, . "Correspondence Analysis in R, with Two- and Three-dimensional Graphics: The ca Package," Journal of Statistical Software, American Statistical Association, vol. 20(i03).
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