Document Detail


Good-Turing frequency estimation in a finite population.
MedLine Citation:
PMID:  25394337     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
Good-Turing frequency estimation (Good, ) is a simple, effective method for predicting detection probabilities of objects of both observed and unobserved classes based on observed frequencies of classes in a sample. The method has been used widely in several disciplines, such as information retrieval, computational linguistics, text recognition, and ecological diversity estimation. Nevertheless, existing studies assume sampling with replacement or sampling from an infinite population, which might be inappropriate for many practical applications. In light of this limitation, this article presents a modification of the Good-Turing estimation method to account for finite population sampling. We provide three practical extensions of the modified method, and we examine performance of the modified method and its extensions in simulation experiments.
Authors:
Wen-Han Hwang; Chih-Wei Lin; Tsung-Jen Shen
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2014-11-12
Journal Detail:
Title:  Biometrical journal. Biometrische Zeitschrift     Volume:  -     ISSN:  1521-4036     ISO Abbreviation:  Biom J     Publication Date:  2014 Nov 
Date Detail:
Created Date:  2014-11-13     Completed Date:  -     Revised Date:  2014-11-14    
Medline Journal Info:
Nlm Unique ID:  7708048     Medline TA:  Biom J     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Copyright Information:
© 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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