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A symbolic data approach for missing values treatment in principal component analysis

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A symbolic data approach for missing values treatment in principal component analysis
Article
journal STATISTICA & APPLICAZIONI
issue STATISTICA & APPLICAZIONI - 2008 - 2
title A symbolic data approach for missing values treatment in principal component analysis
author
publisher Vita e Pensiero
format Article | Pdf
online since 02-2008
issn 18246672 (print)
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There are two ways in order to completely perform a Principal Component Analysis over a data table with missing values: somehow imputating values to the missing data or excluding some part of the original sample from the analysis. Both these solutions can be rather costly, expecially with datasets having an appreciable number of missing values, but only one or at most two missing on any particular observational unit. An alternative proposal is formulated in this paper using the concept of Symbolic Data.

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