Generalization of entropy based divergence measures for symbolic sequence analysis.

ABSTRACT: Entropy based measures have been frequently used in symbolic sequence analysis. A symmetrized and smoothed form of Kullback-Leibler divergence or relative entropy, the Jensen-Shannon divergence (JSD), is of particular interest because of its sharing properties with families of other divergence measures and its interpretability in different domains including statistical physics, information theory and mathematical statistics. The uniqueness and versatility of this measure arise because of a number of attributes including generalization to any number of probability distributions and association of weights to the distributions. Furthermore, its entropic formulation allows its generalization in different statistical frameworks, such as, non-extensive Tsallis statistics and higher order Markovi

SUBMITTER: Re MA 

PROVIDER: S-EPMC3984095 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature