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Rare and Weak models for multiple hypothesis testing assume that only a small proportion of the tested hypotheses concern non-null effects and the individual effects are only moderately large, so they generally do not stand out individually, for example in a Bonferroni analysis.
Feature selection by higher criticism thresholding achieves the optimal phase diagram
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A method of scoring coincidences in tests with playing cards
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Large deviations and exact bahadur’s slope of l-statistics
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Influence functions for testing
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Asymptotic lognormality of p p -values
Lambert, D. and W. Hall (1982) · 1982
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Controlling the false discovery rate: a practical and powerful approach to multiple testing
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On Some Problems of Hypothesis Testing Leading to Infinitely Divisible Distributions
Ingster, J. (1996) · 1996
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Multiple tests with discrete distributions
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Large Deviations Techniques and Applications
Dembo, A. and O. Zeitouni (1998) · 1998
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P values as random variables—expected p values
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Empirical bayes analysis of a microarray experiment
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Probabilities of moderate deviations
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Detecting and estimating sparse mixtures
Jin, J. (2003) · 2003
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Estimating the occurrence of false positives and false negatives in microarray studies by approximating and partitioning the empirical distribution of p-values
Pounds, S. and S. W. Morris (2003) · 2003
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Higher criticism for detecting sparse heterogeneous mixtures
Donoho, D. and J. Jin (2004) · 2004
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Adapting to unknown sparsity by controlling the false discovery rate
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A tutorial on statistical methods for population association studies
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The sparse Poisson means model
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Higher criticism for large-scale inference, especially for rare and weak effects
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The intermediates take it all: Asymptotics of higher criticism statistics and a powerful alternative based on equal local levels
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Hypothesis testing for high-dimensional sparse binary regression
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Genome-wide association study identifies variants at clu and picalm associated with alzheimer’s disease
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Impossibility of successful classification when useful features are rare and weak
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