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A general framework for multiple testing dependence
We develop a general framework for performing large-scale significance testing in the presence of arbitrarily strong dependence. We derive a low-dimensional set of random vectors, called a dependence kernel, that fully captures the dependence structure in an observed high-dimensional dataset. This r...
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| Main Authors: | , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
National Academy of Sciences
2008
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC2586646/ https://ncbi.nlm.nih.gov/pubmed/19033188 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1073/pnas.0808709105 |
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