Abstract

The focus of this thesis is an investigation of ways to detect weak dependence between two random variables X and Y. Our approach is to design tests for correlation rather than testing for dependence directly, since X and Y are not independent if they are not uncorrelated. We examined the magnified Pearson correlation after the Box-Cox transformation to determine whether X and Y are dependent. The results indicated that our approach not only has the potential to detect and evaluate the weak dependence cases that have previously been intractable, but also is conceptually simple and easy to implement.

Degree

PhD

College and Department

Ira A. Fulton College of Engineering and Technology; Electrical and Computer Engineering

Rights

http://lib.byu.edu/about/copyright/

Date Submitted

2011-01-21

Document Type

Dissertation

Handle

http://hdl.lib.byu.edu/1877/etd4184

Keywords

Weak dependence, Box-Cox transformation

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