Linear Non-Gaussian Component Analysis Via Maximum Likelihood

DOI10.1080/01621459.2017.1407772zbMath1478.62155arXiv1511.01609OpenAlexW2962791603MaRDI QIDQ5229915

David Ruppert, Benjamin B. Risk, David S. Matteson

Publication date: 19 August 2019

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1511.01609

zbMATH Keywords

independent component analysisprincipal component analysisprojection pursuitfunctional magnetic resonance imagingneuroimaging

Mathematics Subject Classification ID

Random fields; image analysis (62M40) Factor analysis and principal components; correspondence analysis (62H25) Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric estimation (62G05)

Related Items

Group linear non-Gaussian component analysis with applications to neuroimaging, Locally robust inference for non-Gaussian linear simultaneous equations models, Template Independent Component Analysis with Spatial Priors for Accurate Subject-Level Brain Network Estimation and Inference, Non-Gaussian Component Analysis: Testing the Dimension of the Signal Subspace, Simultaneous non-Gaussian component analysis (SING) for data integration in neuroimaging, Independent component analysis for multivariate functional data, Optimization and testing in linear non‐Gaussian component analysis

Uses Software

• fastICA
• ProDenICA
• neuRosim

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