Canonical Correlation
Canonical correlation is a statistical measure for expressing the relationship between two sets of variables. Formally, given two random vectors x ∈ Rdx and y ∈ Rdy with some joint (unknown) distribution D, the canonical correlation analysis (CCA) seeks vectors u ∈ Rdx and v ∈ Rdy, such that the random vectors when projected along these directions, that is, variables u > x and v > y, are maximally correlated. Equivalently, we can write CCA as the following optimization problem: find u ∈ Rdx, v ∈ Rdy that:
where the correlation, ρ(u > x, v > y), between two random variables, is defined as . Assuming that vectors x and y are 0 mean, we can write CCA as the problem var(u > x) var(u > ...
Looks like you do not have access to this content.
Reader's Guide
Assessment
Cognitive and Affective Variables
Data Visualization Methods
Disabilities and Disorders
Distributions
Educational Policies
Evaluation Concepts
Evaluation Designs
Human Development
Instrument Development
Organizations and Government Agencies
Professional Issues
Publishing
Qualitative Research
Research Concepts
Research Designs
Research Methods
Research Tools
Social and Ethical Issues
Social Network Analysis
Statistics
Teaching and Learning
Theories and Conceptual Frameworks
Threats to Research Validity
- All
- A
- B
- C
- D
- E
- F
- G
- H
- I
- J
- K
- L
- M
- N
- O
- P
- Q
- R
- S
- T
- U
- V
- W
- X
- Y
- Z