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...
| Main Authors: | , , , , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Elsevier
2016
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