Bayesian regularization of Gaussian graphical models with measurement error
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Publication:830423
DOI10.1016/j.csda.2020.107085OpenAlexW3083170245MaRDI QIDQ830423
Monnie McGee, Linh H. Nghiem, Michael Byrd
Publication date: 7 May 2021
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1907.02241
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- Measurement error in Lasso: impact and likelihood bias correction
- Sparse inverse covariance estimation with the graphical lasso
- TIGER: A tuning-insensitive approach for optimally estimating Gaussian graphical models
- Bayesian estimation of sparse signals with a continuous spike-and-slab prior
- On the distribution of the largest eigenvalue in principal components analysis
- A Constrainedℓ1Minimization Approach to Sparse Precision Matrix Estimation
- Model selection and estimation in the Gaussian graphical model
- An Imputation–Regularized Optimization Algorithm for High Dimensional Missing Data Problems and Beyond
- The Spike-and-Slab LASSO
- Simulation‐selection‐extrapolation: Estimation in high‐dimensional errors‐in‐variables models
- Bayesian Regularization for Graphical Models With Unequal Shrinkage
- A Convex Pseudolikelihood Framework for High Dimensional Partial Correlation Estimation with Convergence Guarantees
- Replicates in high dimensions, with applications to latent variable graphical models
- The huge Package for High-dimensional Undirected Graph Estimation in R
- Measurement Error in Nonlinear Models