Estimating the Proportion of True Null Hypotheses: A  Likelihood Approach

Estimating the Proportion of True Null Hypotheses: A Likelihood Approach

Hualing Zhao

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Hanfeng Chen

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Wuhan University of Technology

Estimating the Proportion of True Null Hypotheses: A Likelihood Approach

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Abstract

Many estimators for the proportion of the true null hypotheses in a multiple testing problem have been proposed in literature. Motivated from the work on the histogram approach, in this article we propose a new estimator based on the likelihood function with an approximating alternative histogram. AIC is used to select the number of bins for the histogram. Simulation study demonstrates that the new estimator outperforms and substantially improves existing methods including Storey estimators, convex density estimator, and histogram estimator. The new method is applied to a real-life data set of breast cancer.

References

15 Cites in Article

Reference Format

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Hualing Zhao. 2021. \u201cEstimating the Proportion of True Null Hypotheses: A Likelihood Approach\u201d. Global Journal of Science Frontier Research - F: Mathematics & Decision GJSFR-F Volume 21 (GJSFR Volume 21 Issue F5).

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GJSFR Volume 21 Issue F5

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Journal Specifications

Crossref Journal DOI 10.17406/GJSFR

Print ISSN 0975-5896

e-ISSN 2249-4626

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Classification

GJSFR-F Classification MSC 2010: 97K80

Submission ReceivedSeptember 10, 2021
Peer Review Double Blind
Handling Editor
Accepted October 5, 2021
Published October 16, 2021

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v1.2

Issue date

December 30, 2021

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