A User's Guide to Principal Components
- Authors
- J. Edward Jackson
- Published
- 1991
- DOI
- 10.1002/0471725331
- Citation
- J. Edward Jackson: "A User's Guide to Principal Components", Wiley, 1991.
- Abstract
- Principal component analysis is a multivariate technique in which a number of related variables are transformed to a set of uncorrelated variables. scaling input data, inferential procedures, operations with group data and vector interpretation. Dealing with the how-to-do-it as well as the why-it-works it avoids getting bogged down in theoretical matters and computational techniques focusing instead on practical aspects of data reduction and interpretation.
- Tags
Related items
- Principal component analysis (1987)
- Development of inferential process models using PLS (1994)
- Improvement of processes and product quality through multivariate data analysis (2000)
- Centering and scaling in component analysis (2003)
- Cross-validatory choice of the number of components from a principal component analysis (1982)