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The optimal discovery procedure: A new approach to simultaneous significance testing
John D. Storey
Lewis-Sigler Institute for Integrative Genomics
Molecular Biology
Princeton Institute for Computational Science and Engineering
Center for Statistics & Machine Learning
Research output
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Contribution to journal
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Article
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peer-review
129
Scopus citations
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Dive into the research topics of 'The optimal discovery procedure: A new approach to simultaneous significance testing'. Together they form a unique fingerprint.
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Mathematics
Testing
84%
False Discovery Rate
44%
p-Value
36%
Optimality
28%
Neyman-Pearson Lemma
27%
Multiple Hypothesis Testing
24%
Strategy
24%
Shrinkage Estimation
24%
Significance Test
22%
Paradox
19%
Null Distribution
18%
Hypothesis Testing
17%
Bayesian Approach
16%
Maximise
15%
Tend
12%
Statistics
11%
Alternatives
10%
Performance
10%
Concepts
8%
Business & Economics
Testing
100%
Optimality
33%
P Value
31%
Shrinkage Estimation
21%
Significance Test
18%
Bayesian Approach
14%
Hypothesis Testing
13%
Borrowing
12%
Paradox
10%
Statistics
9%
Alternatives
6%
Performance
5%