ABSTRACT
This paper focuses on applying the method of observed confidence levels to problems commonly encountered in principal component analyses. In particular, we focus on assigning levels of confidence to the number of components that explain a specified proportion of variation in the original data. Approaches based on the normal model as well as a non parametric model are explored. The usefulness of the methods are discussed using an example and an empirical study.
MATHEMATICS SUBJECT CLASSIFICATION:
Acknowledgments
The authors acknowledge the comments of the reviewers which greatly improved the clarity of the presentation of this paper.