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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Auteurs principaux:	Yaohang Lu, Zhongming Teng
Format:	article
Langue:	EN
Publié:	MDPI AG 2021
Sujets:	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
Accès en ligne:	https://doaj.org/article/a226d30d8ec741a4a23804bedfa1a54b
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Robust Bilinear Probabilistic Principal Component Analysis

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