Title :
The maximum likelihood probability of skewed patterns
Author :
Orlitsky, Alan ; Pan, Shengjun
Author_Institution :
ECE & CSE Depts., UCSD, La Jolla, CA, USA
fDate :
June 28 2009-July 3 2009
Abstract :
A pattern is skewed if, as in 11123, one of its symbols repeats and the others appear once. We show that the pattern-maximum-likelihood distribution of essentially all skewed patterns consists of one discrete element whose probability is the fraction of times the repeated symbol appears in the pattern.
Keywords :
discrete systems; maximum likelihood detection; maximum likelihood estimation; probability; discrete element; maximum likelihood probability; skewed patterns; Convergence; Frequency estimation; Genetics; Machine learning; Magnetic heads; Maximum likelihood estimation; Pattern analysis; Probability; Statistical distributions;
Conference_Titel :
Information Theory, 2009. ISIT 2009. IEEE International Symposium on
Conference_Location :
Seoul
Print_ISBN :
978-1-4244-4312-3
Electronic_ISBN :
978-1-4244-4313-0
DOI :
10.1109/ISIT.2009.5206021
