Bayesian scalar-on-tensor regression using the Tucker decomposition for sparse spatial modeling
Daniel Spencer, Rene Gutierrez, Rajarshi Guhaniyogi, Russell T Shinohara et autres
Modeling with multidimensional arrays, or tensors, often presents a problem due to high dimensionality. In addition, these structures typically exhibit inherent sparsity, requiring the use of regularization methods to properly characterize an association between a tensor covariate and a scalar response. We …
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Biostatistics