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Generalized reduced rank latent factor regression for high dimensional tensor fields, and neuroimaging-genetic applications
We propose a generalized reduced rank latent factor regression model (GRRLF) for the analysis of tensor field responses and high dimensional covariates. The model is motivated by the need from imaging-genetic studies to identify genetic variants that are associated with brain imaging phenotypes, oft...
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| Publicado no: | Neuroimage |
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| Main Authors: | , , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2016
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5798650/ https://ncbi.nlm.nih.gov/pubmed/27666385 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.neuroimage.2016.08.027 |
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