## Abstract Principal component analysis (PCA) is a multivariate technique that analyzes a data table in which observations are described by several inter‐correlated quantitative dependent variables. Its goal is to extract the important information from the table, to represent it as a set of new or
Principal Component Analysis
✍ Scribed by I.T. Jolliffe
- Book ID
- 127434804
- Publisher
- Springer
- Year
- 2002
- Tongue
- English
- Weight
- 9 MB
- Edition
- 2nd
- Category
- Library
- ISBN
- 0387954422
No coin nor oath required. For personal study only.
✦ Synopsis
Researchers in statistics, or in other fields that use principal component analysis, will find that the book gives an authoritative yet accessible account of the subject. It is also a valuable resource for graduate courses in multivariate analysis. The book requires some knowledge of matrix algebra.
✦ Subjects
Математическая статистика
📜 SIMILAR VOLUMES
Principal component analysis is central to the study of multivariate data. Although one of the earliest multivariate techniques it continues to be the subject of much research, ranging from new model- based approaches to algorithmic ideas from neural networks. It is extremely versatile with applicat