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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...
Tallennettuna:
| Julkaisussa: | Int J Data Sci Anal |
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| Päätekijät: | , , |
| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
Springer International Publishing
2020
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| Aiheet: | |
| Linkit: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7840662/ https://ncbi.nlm.nih.gov/pubmed/33553594 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s41060-020-00228-y |
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