Exceedance control of the false discovery proportion via high precision inversion method of Berk-Jones statistics

Jeffrey C. Miecznikowski; Jiefei Wang

doi:10.1016/j.csda.2023.107758

Exceedance control of the false discovery proportion via high precision inversion method of Berk-Jones statistics

Jeffrey C. Miecznikowski, Jiefei Wang

Biostatistics & Data Science

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

1 Scopus citations

Abstract

Exceedance control of the false discovery proportion (FDP) can provide an interpretable method for addressing the variability in the false discovery proportion estimates. Exceedance control of FDP can be viewed as constructing a confidence interval for FDP and as such inverting a hypothesis test is a viable method for achieving exceedance control. A novel powerful approach for exceedance control is presented based on using a directional Berk-Jones goodness-of-fit statistic. The approach employs a high-precision implementation procedure to accurately compute confidence envelopes for FDP. The procedure is compared against other methods and generalized to include other goodness-of-fit statistics that follow an isotropy condition.

Original language	English (US)
Article number	107758
Journal	Computational Statistics and Data Analysis
Volume	185
DOIs	https://doi.org/10.1016/j.csda.2023.107758
State	Published - Sep 2023

Keywords

Berk-Jones statistic
Confidence envelope
Exceedance control
False discovery proportion

ASJC Scopus subject areas

Statistics and Probability
Computational Mathematics
Computational Theory and Mathematics
Applied Mathematics

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10.1016/j.csda.2023.107758

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title = "Exceedance control of the false discovery proportion via high precision inversion method of Berk-Jones statistics",

abstract = "Exceedance control of the false discovery proportion (FDP) can provide an interpretable method for addressing the variability in the false discovery proportion estimates. Exceedance control of FDP can be viewed as constructing a confidence interval for FDP and as such inverting a hypothesis test is a viable method for achieving exceedance control. A novel powerful approach for exceedance control is presented based on using a directional Berk-Jones goodness-of-fit statistic. The approach employs a high-precision implementation procedure to accurately compute confidence envelopes for FDP. The procedure is compared against other methods and generalized to include other goodness-of-fit statistics that follow an isotropy condition.",

keywords = "Berk-Jones statistic, Confidence envelope, Exceedance control, False discovery proportion",

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year = "2023",

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T1 - Exceedance control of the false discovery proportion via high precision inversion method of Berk-Jones statistics

AU - Miecznikowski, Jeffrey C.

AU - Wang, Jiefei

PY - 2023/9

Y1 - 2023/9

N2 - Exceedance control of the false discovery proportion (FDP) can provide an interpretable method for addressing the variability in the false discovery proportion estimates. Exceedance control of FDP can be viewed as constructing a confidence interval for FDP and as such inverting a hypothesis test is a viable method for achieving exceedance control. A novel powerful approach for exceedance control is presented based on using a directional Berk-Jones goodness-of-fit statistic. The approach employs a high-precision implementation procedure to accurately compute confidence envelopes for FDP. The procedure is compared against other methods and generalized to include other goodness-of-fit statistics that follow an isotropy condition.

AB - Exceedance control of the false discovery proportion (FDP) can provide an interpretable method for addressing the variability in the false discovery proportion estimates. Exceedance control of FDP can be viewed as constructing a confidence interval for FDP and as such inverting a hypothesis test is a viable method for achieving exceedance control. A novel powerful approach for exceedance control is presented based on using a directional Berk-Jones goodness-of-fit statistic. The approach employs a high-precision implementation procedure to accurately compute confidence envelopes for FDP. The procedure is compared against other methods and generalized to include other goodness-of-fit statistics that follow an isotropy condition.

KW - Berk-Jones statistic

KW - Confidence envelope

KW - Exceedance control

KW - False discovery proportion

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JO - Computational Statistics and Data Analysis

JF - Computational Statistics and Data Analysis

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ER -

Exceedance control of the false discovery proportion via high precision inversion method of Berk-Jones statistics

Abstract

Keywords

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