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Comparison of bias-reducing methods for estimating the parameter in dilution series

 

作者: Leo W. G. Strijbosch,   Ronald J. M. M. Does,  

 

期刊: Communications in Statistics - Simulation and Computation  （Taylor Available online 1988）
卷期: Volume 17, issue 4  

页码: 1173-1190

 

ISSN:0361-0918

 

年代: 1988

 

DOI:10.1080/03610918808812719

 

出版商: Marcel Dekker, Inc.

 

关键词: limiting and serial dilution assays;maximum likelihood;jackknife methods;bootstrap methods;min-imum cht-square;Monte Carlo experiments;experimental design

 

数据来源: Taylor

 

摘要:

Ten different estimators of the parameter in a limiting or serial dilution assay are compared. Eight of them are constructed to reduce the bias of the commonly used maximum likelihood estimator. Extensive Monte Carlo experiments using various designs, and practical considerations, suggest that a particular jackknife version of the maximum likelihood estimator is preferred, provided that the design is not too small.

 

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