Shrinkage estimation of proportion via logit penalty

Yoonsuh Jung

doi:10.1080/03610926.2015.1048881

Shrinkage estimation of proportion via logit penalty

Research output: Contribution to journal › Article › peer-review

Abstract

By releasing the unbiasedness condition, we often obtain more accurate estimators due to the bias–variance trade-off. In this paper, we propose a class of shrinkage proportion estimators which show improved performance over the sample proportion. We provide the “optimal” amount of shrinkage. The advantage of the proposed estimators is given theoretically as well as explored empirically by simulation studies and real data analyses.

Original language	English
Pages (from-to)	2447-2453
Number of pages	7
Journal	Communications in Statistics - Theory and Methods
Volume	46
Issue number	5
DOIs	https://doi.org/10.1080/03610926.2015.1048881
Publication status	Published - 2017 Mar 4
Externally published	Yes

Keywords

Biased estimator
penalization
sample proportion
shrinkage proportion estimator

ASJC Scopus subject areas

Statistics and Probability

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10.1080/03610926.2015.1048881

Cite this

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Shrinkage estimation of proportion via logit penalty

Abstract

Keywords

ASJC Scopus subject areas

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