Estimating Entropy

William Bialek, Jonathan Miller

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Entropy estimation, which plays a central role in the analysis of biological data is discussed. Small improvements in estimates of relative entropy can yield significant rewards in the quality of sequence alignments. Estimation must be carried out in a regime where the possibilities are not exhausted by the data. It is found that within a Bayesian approach, the best possible estimates based on the data can be made by using a uniform entropic prior- one that reflects minimal a priori assumptions about the entropy.

Original languageEnglish (US)
Title of host publicationProceedings of the 6th Joint Conference on Information Sciences, JCIS 2002
EditorsJ.H. Caulfield, S.H. Chen, H.D. Cheng, R. Duro, J.H. Caufield, S.H. Chen, H.D. Cheng, R. Duro, V. Honavar
Number of pages1
Volume6
StatePublished - Dec 1 2002
EventProceedings of the 6th Joint Conference on Information Sciences, JCIS 2002 - Research Triange Park, NC, United States
Duration: Mar 8 2002Mar 13 2002

Other

OtherProceedings of the 6th Joint Conference on Information Sciences, JCIS 2002
CountryUnited States
CityResearch Triange Park, NC
Period3/8/023/13/02

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

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  • Cite this

    Bialek, W., & Miller, J. (2002). Estimating Entropy. In J. H. Caulfield, S. H. Chen, H. D. Cheng, R. Duro, J. H. Caufield, S. H. Chen, H. D. Cheng, R. Duro, & V. Honavar (Eds.), Proceedings of the 6th Joint Conference on Information Sciences, JCIS 2002 (Vol. 6)