Bayesian variable selection for globally sparse probabilistic PCA

DOI10.1214/18-EJS1450zbMath1412.62077arXiv1605.05918OpenAlexW2375894707WikidataQ129248244 ScholiaQ129248244MaRDI QIDQ1786585

Pierre Latouche, Charles Bouveyron, Pierre-Alexandre Mattei

Publication date: 24 September 2018

Published in: Electronic Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1605.05918

zbMATH Keywords

unsupervised learningprincipal componentsvariable selectionsparsity

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Statistical ranking and selection procedures (62F07)

Related Items (4)

Multiplying a Gaussian matrix by a Gaussian vector ⋮ Prediction and estimation consistency of sparse multi-class penalized optimal scoring ⋮ Bayesian variable selection for globally sparse probabilistic PCA ⋮ GSPPCA

Uses Software

• R
• Algorithm 644
• spinyReg
• GitHub
• ReactomePA
• PCANet
• PRMLT

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