Regularized 3D functional regression for brain image data via Haar wavelets

DOI10.1214/14-AOAS736zbMath1454.62415arXiv1407.8401WikidataQ30973712 ScholiaQ30973712MaRDI QIDQ400650

Bin Nan, Xuejing Wang, Robert Koeppe, Ji Zhu

Publication date: 22 August 2014

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1407.8401

zbMATH Keywords

Haar waveletvariable selectionfunctional data analysisLassoAlzheimer's diseasebrain imagingPET image

Mathematics Subject Classification ID

Functional data analysis (62R10) Applications of statistics to biology and medical sciences; meta analysis (62P10) Biomedical imaging and signal processing (92C55)

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Uses Software

• fda (R)

Cites Work

• Unnamed Item
• The Adaptive Lasso and Its Oracle Properties
• Functional linear regression that's interpretable
• Penalized wavelets: embedding wavelets into semiparametric regression
• Simultaneous analysis of Lasso and Dantzig selector
• Pathwise coordinate optimization
• On the ``degrees of freedom of the lasso
• The Dantzig selector: statistical estimation when \(p\) is much larger than \(n\). (With discussions and rejoinder).
• Coordinate descent algorithms for lasso penalized regression
• Functional data analysis.
• Multivariable Model‐Building
• Functional Generalized Linear Models with Images as Predictors
• An iterative thresholding algorithm for linear inverse problems with a sparsity constraint
• Meta Analysis of Functional Neuroimaging Data via Bayesian Spatial Point Processes
• A Primer on Wavelets and Their Scientific Applications