Bias-corrected estimators for proportion of true null hypotheses: application of adaptive FDR-controlling in segmented failure data

DOI10.1080/02664763.2021.1957790OpenAlexW3183250266WikidataQ114641818 ScholiaQ114641818MaRDI QIDQ5044668

Gaurangadeb Chattopadhyay, Aniket Biswas, Aditya Chatterjee

Publication date: 2 November 2022

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2007.13099

zbMATH Keywords

\(p\)-valuemultiple hypotheses testingadaptive Benjamini-Hochberg algorithmmean mileage to failure

Mathematics Subject Classification ID

Applications of statistics in engineering and industry; control charts (62P30) Parametric inference (62F99) Survival analysis and censored data (62N99) Applications of statistics (62Pxx)

Related Items (1)

New results for adaptive false discovery rate control with \(p\)-value weighting

Uses Software

• SAM
• cp4p

Cites Work

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• On methods controlling the false discovery rate
• Adaptive FDR control under independence and dependence
• Adaptive linear step-up procedures that control the false discovery rate
• The Behavior of the P-Value When the Alternative Hypothesis is True
• Statistical Analysis of Product Warranty Data*
• Strong Control, Conservative Point Estimation and Simultaneous Conservative Consistency of False Discovery Rates: A Unified Approach
• A Direct Approach to False Discovery Rates
• Estimating the proportion of true null hypotheses with application in microarray data
• Estimating the proportion of true null hypotheses using the pattern of observedp-values
• Estimating the Proportion of True Null Hypotheses, with application to DNA Microarray Data

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