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5. Conclusion
Very much in vogue in the 1970s and 1980s, current research does not call into question the main principles and methodological foundations of these different methods, as described in this article and implemented in most commercial software with only minor differences in graphical representation options. Nevertheless, ongoing reflection and recent or future developments are concerned with the problems of adapting to new types of data (functional data, spectra...) or with the difficulties arising with very large-scale tables, as is the case with so-called post-genomic data or data from the Internet during technology watch.
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Conclusion
Bibliography
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Other resources (handouts, practical exercises, functions written in R) are available on the website :
https://www.math.univ-toulouse.fr/
R Development Core TeamR: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing
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The most useful general and introductory references for this theme are: Bouroche & Saporta (1980), Jobson (1992), Lebart, Morineau & Piron (2006), Mardia, Kent & Bibby (1979), Saporta (2006). More recent additions and developments can be found in: Droesbeke, Fichet & Tassi (1992), Govaert (2003).
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