Canonical Correlation Analysis

Wolfgang Karl Härdle () and Leopold Simar
Additional contact information
Wolfgang Karl Härdle: Humboldt-Universität zu Berlin, Ladislaus von Bortkiewicz Chair of Statistics

Chapter Chapter 16 in Applied Multivariate Statistical Analysis, 2019, pp 431-442 from Springer

Abstract: Abstract Complex multivariate dataCanonical correlation analysis structures are better understood by studying low-dimensional projections. For a joint study of two data sets, we may ask what type of low-dimensional projection helps in finding possible joint structures for the two samples. The canonical correlation analysis is a standard tool of multivariate statistical analysis for discovery and quantification of associations between two sets of variables.

Date: 2019
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
Chapter: Canonical Correlation Analysis (2024)
Chapter: Canonical Correlation Analysis (2015)
Chapter: Canonical Correlation Analysis (2003)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-26006-4_16

Ordering information: This item can be ordered from
http://www.springer.com/9783030260064

DOI: 10.1007/978-3-030-26006-4_16

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().