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Least squares and maximum likelihood estimation of sufficient reductions in regressions with matrix-valued predictors
We propose methods to estimate sufficient reductions in matrix-valued predictors for regression or classification. We assume that the first moment of the predictor matrix given the response can be decomposed into a row and column component via a Kronecker product structure. We obtain least squares a...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer International Publishing
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7840662/ https://www.ncbi.nlm.nih.gov/pubmed/33553594 http://dx.doi.org/10.1007/s41060-020-00228-y |