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MEASURING DEPENDENCE VIA MUTUAL INFORMATION
 

Summary: MEASURING DEPENDENCE VIA MUTUAL
INFORMATION
by
Shan Lu
A thesis submitted to the
Department of Mathematics and Statistics
in conformity with the requirements for
the degree of Master of Science
Queen's University
Kingston, Ontario, Canada
September 2011
Copyright c Shan Lu, 2011
Abstract
Considerable research has been done on measuring dependence between random vari-
ables. The correlation coefficient [10] is the most widely studied linear measure of
dependence. However, the limitation of linearity limits its application. The informa-
tional coefficient of correlation [17] is defined in terms of mutual information. It also
has some deficiencies, such as it is only normalized to continuous random variables.
Based on the concept of the informational coefficient of correlation, a new depen-
dence measure, which we call the L-measure, is proposed in this work which general-

  

Source: Alajaji, Fady - Department of Mathematics and Statistics, Queen's University (Kingston)

 

Collections: Engineering