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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...

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Detalles Bibliográficos
Autores principales:	Pfeiffer, Ruth M., Kapla, Daniel B., Bura, Efstathia
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Springer International Publishing 2020
Materias:	Regular Paper
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

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