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

Magazine

STATISTICA & APPLICAZIONI

Section

Open Access

Title

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

Author

Paola Zuccolotto

Publisher

Vita e Pensiero

Format

Article |

Pdf

Online from

02-2008

Issn

1824-6672 (print) | 2283-6659 (digital)

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Description Readers' comments

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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