Semi‐supervised empirical Bayes group‐regularized factor regression-Reference-Cited by-同舟云学术

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Semi‐supervised empirical Bayes group‐regularized factor regression

Published:2022-06-22 Issue:7 Volume:64 Page:1289-1306
ISSN:0323-3847
Container-title:Biometrical Journal
language:en
Short-container-title:Biometrical J

Author:

Münch Magnus M.¹²,van de Wiel Mark A.¹³,van der Vaart Aad W.⁴,Peeters Carel F. W.¹⁵

Affiliation:

1. Department of Epidemiology & Data Science Amsterdam UMC Amsterdam The Netherlands

2. Mathematical Institute Leiden University Leiden The Netherlands

3. MRC Biostatistics Unit Cambridge Institute of Public Health Cambridge UK

4. Delft Institute of Applied Mathematics ‐ TU Delft DelftThe Netherlands

5. Mathematical & Statistical Methods Group (Biometris) Wageningen University & Research Wageningen The Netherlands

Publisher

Wiley

Subject

Statistics, Probability and Uncertainty,General Medicine,Statistics and Probability

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/bimj.202100105

Reference29 articles.

1. How to determine the number of factors to retain in exploratory factor analysis: A comparison of extraction methods under realistic conditions.

2. Avalos‐Pacheco A. Rossell D. &Savage R. S.(2022).Heterogeneous large datasets integration using Bayesian factor regression.Bayesian Analysis 17(1) 33–66.

3. MAXIMUM LIKELIHOOD ESTIMATION OF FACTOR MODELS ON DATASETS WITH ARBITRARY PATTERN OF MISSING DATA

4. NCBI GEO: archive for functional genomics data sets—update

5. Variational Inference: A Review for Statisticians

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