Sparse Principal Component Analysis (sparse PCA) represents a significant advance in the field of dimensionality reduction for high-dimensional data. Unlike conventional Principal Component Analysis ...
This article presents and compares two approaches of principal component (PC) analysis for two-dimensional functional data on a possibly irregular domain. The first approach applies the singular value ...
This is a preview. Log in through your library . Abstract We develop new statistical theory for probabilistic principal component analysis models in high dimensions. The focus is the estimation of the ...
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