On Measure Transformed Canonical Correlation Analysis

Details On Measure Transformed Canonical Correlation Analysis On Measure Transformed Canonical Correlation Analysis

2011-11-27

arxiv.org/abs/1111.6308v3

Statistics

Methodology

Scientific paper

In this paper linear canonical correlation analysis (LCCA) is generalized by applying a structured transform to the joint probability distribution of the considered pair of random vectors, i.e., a transformation of the joint probability measure defined on their joint observation space. This framework, called measure transformed canonical correlation analysis (MTCCA), applies LCCA to the data after transformation of the joint probability measure. We show that judicious choice of the transform leads to a modified canonical correlation analysis, which, in contrast to LCCA, is capable of detecting non-linear relationships between the considered pair of random vectors. Unlike kernel canonical correlation analysis, where the transformation is applied to the random vectors, in MTCCA the transformation is applied to their joint probability distribution. This results in performance advantages and reduced implementation complexity. The proposed approach is illustrated for graphical model selection in simulated data having non-linear dependencies, and for measuring long-term associations between companies traded in the NASDAQ and NYSE stock markets.

Affiliated with

Also associated with

No associations

Rating

On Measure Transformed Canonical Correlation Analysis does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with On Measure Transformed Canonical Correlation Analysis, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and On Measure Transformed Canonical Correlation Analysis will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-66683