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Robust correspondence analysis

Riani, Marco, Atkinson, Anthony C., Torti, Francesca and Corbellini, Aldo (2022) Robust correspondence analysis. Journal of the Royal Statistical Society. Series C: Applied Statistics. ISSN 0035-9254

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Identification Number: 10.1111/rssc.12580

Abstract

Correspondence analysis is a method for the visual display of information from two-way contingency tables. We introduce a robust form of correspondence analysis based on minimum covariance determinant estimation. This leads to the systematic deletion of outlying rows of the table and to plots of greatly increased informativeness. Our examples are trade flows of clothes and consumer evaluations of the perceived properties of cars. The robust method requires that a specified proportion of the data be used in fitting. To accommodate this requirement we provide an algorithm that uses a subset of complete rows and one row partially, both sets of rows being chosen robustly. We prove the convergence of this algorithm.

Item Type: Article
Official URL: https://rss.onlinelibrary.wiley.com/journal/146798...
Additional Information: © 2022 The Authors
Divisions: Statistics
Subjects: H Social Sciences > HA Statistics
Date Deposited: 14 Jun 2022 11:36
Last Modified: 14 Sep 2022 14:45
URI: http://eprints.lse.ac.uk/id/eprint/115368

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