Please note: In order to keep Hive up to date and provide users with the best features, we are no longer able to fully support Internet Explorer. The site is still available to you, however some sections of the site may appear broken. We would encourage you to move to a more modern browser like Firefox, Edge or Chrome in order to experience the site fully.

Principal Component Analysis, Hardback Book

Principal Component Analysis Hardback

Part of the Springer Series in Statistics series

Hardback

Description

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 applications in many disciplines.

The first edition of this book was the first comprehensive text written solely on principal component analysis.

The second edition updates and substantially expands the original version, and is once again the definitive text on the subject.

It includes core material, current research and a wide range of applications.

Its length is nearly double that of the first edition.

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. Ian Jolliffe is Professor of Statistics at the University of Aberdeen.

He is author or co-author of over 60 research papers and three other books.

His research interests are broad, but aspects of principal component analysis have fascinated him and kept him busy for over 30 years.

Information

Other Formats

£219.99

 
Free Home Delivery

on all orders

 
Pick up orders

from local bookshops

Information

Also in the Springer Series in Statistics series  |  View all