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Convergence of Chao Unseen Species Estimator
Published in Institute of Electrical and Electronics Engineers Inc.
2019
Volume: 2019-July
   
Pages: 46 - 50
Abstract
Support size estimation and the related problem of unseen species estimation have wide applications in ecology and database analysis. Perhaps the most used support size estimator is the Chao estimator. Despite its widespread use, little is known about its theoretical properties. We analyze the Chao estimator and show that its worst case mean squared error (MSE) is smaller than the MSE of the plug-in estimator by a factor of O k/n2. Our main technical contribution is a new method to analyze rational estimators for discrete distribution properties, which may be of independent interest. © 2019 IEEE.
About the journal
JournalData powered by TypesetIEEE International Symposium on Information Theory - Proceedings
PublisherData powered by TypesetInstitute of Electrical and Electronics Engineers Inc.
ISSN21578095
Open AccessYes
Concepts (8)
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    Mean square error
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    DATABASE ANALYSIS
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    DISCRETE DISTRIBUTION
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    Mean squared error
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    PLUG-IN ESTIMATORS
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    SIZE ESTIMATION
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    Technical contribution
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    Information theory