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An Orthogonally Equivariant Estimator of the Covariance Matrix in High Dimensions and for Small Sample Sizes

We introduce an estimation method of covariance matrices in a high-dimensional setting, i.e., when the dimension of the matrix, p, is larger than the sample size n. Specifically, we propose an orthogonally equivariant estimator. The eigenvectors of such estimator are the same as those of the sample...

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Detalhes bibliográficos
Publicado no:J Stat Plan Inference
Main Authors: Banerjee, Samprit, Monni, Stefano
Formato: Artigo
Idioma:Inglês
Publicado em: 2020
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC7709931/
https://ncbi.nlm.nih.gov/pubmed/33281277
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.jspi.2020.10.006
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