Mixtures of robust probabilistic principal component analyzers
✍ Scribed by Cédric Archambeau; Nicolas Delannay; Michel Verleysen
- Book ID
- 113815703
- Publisher
- Elsevier Science
- Year
- 2008
- Tongue
- English
- Weight
- 643 KB
- Volume
- 71
- Category
- Article
- ISSN
- 0925-2312
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📜 SIMILAR VOLUMES
This paper is concerned with a study of robust estimation in principal component analysis. A class of robust estimators which are characterized as eigenvectors of weighted sample covariance matrices is proposed, where the weight functions recursively depend on the eigenvectors themselves. Also, a fe
Robust estimates of principal components are developed using appropriate deÿnitions of multivariate signs and ranks. Simulations and a data example are used to compare these methods to the regular method and one based on the minimum-volume-ellipsoid estimate of the covariance matrix. The sign and ra