Principal components analysis for mixtures with varying concentrations
Principal Component Analysis (PCA) is a classical technique of dimension reduction for multivariate data. When the data are a mixture of subjects from different subpopulations one can be interested in PCA of some (or each) subpopulation separately. In this paper estimators are considered for PC dire...
Guardado en:
Autores principales: | Olena Sugakova, Rostyslav Maiboroda |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
VTeX
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/e5c2e87d921840a693dcf03bb32adde1 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Editorial Board
Publicado: (2021) -
Corrigendum to “Modeling and image quality enhancement for dynamic compressive imaging system”
Publicado: (2021) -
Circulant preconditioners for mean curvature-based image deblurring problem
por: Shahbaz Ahmad, et al.
Publicado: (2021) -
Modeling and image quality enhancement for dynamic compressive imaging system
por: Changjun Zha*, et al.
Publicado: (2021) -
Differential Evolution Evolved RBFNN based automated recognition of Traffic Sign Images
por: Manasa R., et al.
Publicado: (2021)