Exploratory multivariate data analysis from its origins to 1980: nine contributions.
Lebart, Ludovic (2008)
Journal Électronique d'Histoire des Probabilités et de la Statistique [electronic only]
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Lebart, Ludovic (2008)
Journal Électronique d'Histoire des Probabilités et de la Statistique [electronic only]
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Michael Friendly, Daniel Denis (2000)
Journal de la société française de statistique
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Gower, John (2008)
Journal Électronique d'Histoire des Probabilités et de la Statistique [electronic only]
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Daniel Defays (1997)
Qüestiió
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A natural strategy to protect the confidentiality of individual data is to aggregate them at the lowest possible level. Some studies realised in Eurostat on this topic will be presented: properties of classifications in clusters of fixed sizes, micro-aggregation as a generic method to protect the confidentiality of individual data, application to the Community Innovation Survey. The work performed in Eurostat will be put in line with other projects conducted at European level on the...
Angela Montanari, Stefania Mignani (1994)
Qüestiió
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The problem of missing data is particularly present in archaeological research where, because of the fragmentariness of the finds, only a part of the characteristics of the whole object can be observed. The performance of various dissimilarity indices differently weighting missing values is studied on archaeological data via a simulation. An alternative solution consisting in randomly substituting missing values with character sets is also examined. Gower's dissimilarity coefficient...
Adalbert F. X. Wilhelm (2000)
Journal de la société française de statistique
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de Falguerolles, Antoine (2008)
Journal Électronique d'Histoire des Probabilités et de la Statistique [electronic only]
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Murtagh, Fionn (2008)
Journal Électronique d'Histoire des Probabilités et de la Statistique [electronic only]
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Camiz, Sergio (2008)
Bulletin of TICMI
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Ganesh, Siva (1997)
Journal of Applied Mathematics and Decision Sciences
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Antonio Ciampi, Ana González Marcos, Manuel Castejón Limas (2005)
SORT
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Correspondence analysis followed by clustering of both rows and columns of a data matrix is proposed as an approach to two-way clustering. The novelty of this contribution consists of: i) proposing a simple method for the selecting of the number of axes; ii) visualizing the data matrix as is done in micro-array analysis; iii) enhancing this representation by emphasizing those variables and those individuals which are 'well represented' in the subspace of the chosen axes. The approach...