Optimal designs in sparse linear models
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Publication:2303755
DOI10.1007/s00184-019-00722-9zbMath1441.62198OpenAlexW2951686317MaRDI QIDQ2303755
Xiangshun Kong, Ming-Yao Ai, Yi-min Huang
Publication date: 5 March 2020
Published in: Metrika (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s00184-019-00722-9
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- On asymptotically optimal confidence regions and tests for high-dimensional models
- Sparse inverse covariance estimation with the graphical lasso
- Bayesian \(T\)-optimal discriminating designs
- General equivalence theory for optimum designs (approximate theory)
- Optimal discrimination designs
- Bayesian D-optimal supersaturated designs
- Confidence Intervals and Hypothesis Testing for High-Dimensional Regression
- A Constrainedℓ1Minimization Approach to Sparse Precision Matrix Estimation
- Square-root lasso: pivotal recovery of sparse signals via conic programming
- An Algorithmic Approach to Constructing Supersaturated Designs
- Scaled sparse linear regression
- A Comparison of Algorithms for Constructing Exact D-Optimal Designs
- Columnwise-Pairwise Algorithms with Applications to the Construction of Supersaturated Designs
- Confidence Intervals for Low Dimensional Parameters in High Dimensional Linear Models
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