On generalized latent factor modeling and inference for high‐dimensional binomial data-Reference-Cited by-同舟云学术

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On generalized latent factor modeling and inference for high‐dimensional binomial data

Published:2022-10-25 Issue: Volume: Page:
ISSN:0006-341X
Container-title:Biometrics
language:en
Short-container-title:Biometrics

Author:

Ma Ting Fung¹^ORCID,Wang Fangfang²^ORCID,Zhu Jun³^ORCID

Affiliation:

1. Department of Statistics University of South Carolina Columbia South Carolina USA

2. Department of Mathematical Sciences Worcester Polytechnic Institute Worcester Massachusetts USA

3. Department of Statistics University of Wisconsin‐Madison Madison Wisconsin USA

Funder

U.S. Geological Survey

Publisher

Wiley

Subject

Applied Mathematics,General Agricultural and Biological Sciences,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,Statistics and Probability

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/biom.13768

Reference43 articles.

1. Regularization of Wavelet Approximations

2. Principal components estimation and identification of static factors

3. Controlling the false discovery rate: A practical and powerful approach to multiple testing;Benjamini Y.;Journal of the Royal Statistical Society, Series B,1995

4. Genome-Wide Association Studies

5. Adaptive Thresholding for Sparse Covariance Matrix Estimation

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