Robust Bilinear Probabilistic Principal Component Analysis

Principal component analysis (PCA) is one of the most popular tools in multivariate exploratory data analysis. Its probabilistic version (PPCA) based on the maximum likelihood procedure provides a probabilistic manner to implement dimension reduction. Recently, the bilinear PPCA (BPPCA) model, which...

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Detalles Bibliográficos
Autores principales:	Yaohang Lu, Zhongming Teng
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	2-D data probabilistic principal component analysis AECM algorithm matrix variate Gaussian distributions matrix variate <i>t</i> distributions outliers Industrial engineering. Management engineering T55.4-60.8 Electronic computers. Computer science QA75.5-76.95
Acceso en línea:	https://doaj.org/article/a226d30d8ec741a4a23804bedfa1a54b
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Robust Bilinear Probabilistic Principal Component Analysis

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