Robust Bilinear Probabilistic Principal Component Analysis

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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Bibliographic Details
Main Authors: Yaohang Lu, Zhongming Teng
Format: Article
Language:English
Published: MDPI AG 2021-11-01
Series:Algorithms
Subjects:
2-D data
probabilistic principal component analysis
AECM algorithm
matrix variate Gaussian distributions
matrix variate <i>t</i> distributions
outliers
Online Access:https://www.mdpi.com/1999-4893/14/11/322

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https://www.mdpi.com/1999-4893/14/11/322

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