Sparse Bayesian linear regression using generalized normal priors
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Publication:5272445
DOI10.1142/S0219691317500217zbMath1365.62287OpenAlexW2587925907MaRDI QIDQ5272445
Puyu Wang, Qing Dong, Hai Zhang, Pu. Wang
Publication date: 29 June 2017
Published in: International Journal of Wavelets, Multiresolution and Information Processing (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1142/s0219691317500217
Uses Software
Cites Work
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- Shrinkage regression for multivariate inference with missing data, and an application to portfolio balancing
- Reversible jump Markov chain Monte Carlo computation and Bayesian model determination
- Sparse inverse covariance estimation with the graphical lasso
- The Adaptive Lasso and Its Oracle Properties
- The essential ability of sparse reconstruction of different compressive sensing strategies
- A Bayesian lasso via reversible-jump MCMC
- Enhancing sparsity by reweighted \(\ell _{1}\) minimization
- Estimating the dimension of a model
- Least angle regression. (With discussion)
- Pathwise coordinate optimization
- Inference with normal-gamma prior distributions in regression problems
- The horseshoe estimator for sparse signals
- The Bayesian Lasso
- Bayesian lasso regression
- On scale mixtures of normal distributions
- 10.1162/15324430152748236
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- Sparsity and Smoothness Via the Fused Lasso
- BAYESIAN REGRESSION ANALYSIS WITH SCALE MIXTURES OF NORMALS
- L 1/2 regularization
- Model Selection and Estimation in Regression with Grouped Variables
- Ridge Regression: Biased Estimation for Nonorthogonal Problems
- Ridge Regression: Applications to Nonorthogonal Problems
- Prior distributions for variance parameters in hierarchical models (Comment on article by Browne and Draper)
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