Stability of robust and non-robust principal components analysis
✍ Scribed by Ramses Abul Naga; Gérard Antille
- Publisher
- Elsevier Science
- Year
- 1990
- Tongue
- English
- Weight
- 377 KB
- Volume
- 10
- Category
- Article
- ISSN
- 0167-9473
No coin nor oath required. For personal study only.
📜 SIMILAR VOLUMES
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
## Abstract Ecological studies frequently involve large numbers of variables and observations, and these are often subject to various errors. If some data are not representative of the study population, they tend to bias the interpretation and conclusion of an ecological study. Because of the multi
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