Fast and covariate-adaptive method amplifies detection power in large-scale multiple hypothesis testing
Side information in addition to the p-values is often available in modern applications of multiple hypothesis testing. Here, the authors develop AdaFDR, a new statistical method for multiple hypothesis testing that adaptively learns the decision threshold and amplifies the discovery power.
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| Autores principales: | , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2019
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/857c63f9248a49b7a4152050747075ac |
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