Pages that link to "Item:Q3512676"
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The following pages link to Model selection and estimation in the Gaussian graphical model (Q3512676):
Displaying 50 items.
- Robust sparse Gaussian graphical modeling (Q2404420) (← links)
- Node-structured integrative Gaussian graphical model guided by pathway information (Q2405417) (← links)
- Regularized estimation in sparse high-dimensional multivariate regression, with application to a DNA methylation study (Q2406186) (← links)
- The degrees of freedom of partly smooth regularizers (Q2409395) (← links)
- Multilevel Gaussian graphical model for multilevel networks (Q2409630) (← links)
- Large covariance estimation through elliptical factor models (Q2413594) (← links)
- AIC for the non-concave penalized likelihood method (Q2414941) (← links)
- Structure learning of sparse directed acyclic graphs incorporating the scale-free property (Q2418068) (← links)
- D-trace estimation of a precision matrix using adaptive lasso penalties (Q2418368) (← links)
- Graph-based sparse linear discriminant analysis for high-dimensional classification (Q2418517) (← links)
- Variable selection procedures from multiple testing (Q2423858) (← links)
- Blessing of massive scale: spatial graphical model estimation with a total cardinality constraint approach (Q2425168) (← links)
- Penalized model-based clustering (Q2426832) (← links)
- Penalized estimation in high-dimensional hidden Markov models with state-specific graphical models (Q2441854) (← links)
- Structure estimation for discrete graphical models: generalized covariance matrices and their inverses (Q2443211) (← links)
- Robust concentration graph model selection (Q2445761) (← links)
- Regularized multivariate regression models with skew-\(t\) error distributions (Q2448807) (← links)
- Graphical model selection and estimation for high dimensional tensor data (Q2451627) (← links)
- Random matrix theory in statistics: a review (Q2453609) (← links)
- Hierarchical array priors for ANOVA decompositions of cross-classified data (Q2453654) (← links)
- A SINful approach to Gaussian graphical model selection (Q2474398) (← links)
- Sparse estimation of large covariance matrices via a nested Lasso penalty (Q2482977) (← links)
- Strong oracle optimality of folded concave penalized estimation (Q2510819) (← links)
- Convergence and sparsity of Lasso and group Lasso in high-dimensional generalized linear models (Q2516626) (← links)
- Sparse reduced-rank regression with covariance estimation (Q2631378) (← links)
- Bayesian sparse covariance decomposition with a graphical structure (Q2631381) (← links)
- On the impact of contaminations in graphical Gaussian models (Q2655558) (← links)
- Differentially private precision matrix estimation (Q2663280) (← links)
- Bayesian analysis of nonparanormal graphical models using rank-likelihood (Q2676906) (← links)
- An integrated precision matrix estimation for multivariate regression problems (Q2676914) (← links)
- Precision matrix estimation using penalized generalized Sylvester matrix equation (Q2677125) (← links)
- Kronecker-structured covariance models for multiway data (Q2678238) (← links)
- Network-based discriminant analysis for multiclassification (Q2680180) (← links)
- Testing and support recovery of correlation structures for matrix-valued observations with an application to stock market data (Q2682965) (← links)
- A Bayesian graphical approach for large-scale portfolio management with fewer historical data (Q2686273) (← links)
- Regularised MANOVA for high-dimensional data (Q2802885) (← links)
- Efficient estimation of covariance selection models (Q2813897) (← links)
- A Gaussian graphical model approach to climate networks (Q2821530) (← links)
- Estimation of sparse directed acyclic graphs for multivariate counts data (Q2827189) (← links)
- Tests for mean vectors in high dimension (Q2870766) (← links)
- Topology selection in graphical models of autoregressive processes (Q2896161) (← links)
- Tuning parameter selection for penalized likelihood estimation of Gaussian graphical model (Q2905113) (← links)
- Partial correlation matrix estimation using ridge penalty followed by thresholding and re-estimation (Q2927635) (← links)
- Robust and Sparse Estimation of the Inverse Covariance Matrix Using Rank Correlation Measures (Q2963607) (← links)
- Learning Oncogenic Pathways from Binary Genomic Instability Data (Q3008875) (← links)
- Regularized Parameter Estimation in High-Dimensional Gaussian Mixture Models (Q3016190) (← links)
- A Nonparametric Graphical Model for Functional Data With Application to Brain Networks Based on fMRI (Q3121557) (← links)
- Identifying small mean-reverting portfolios (Q3169214) (← links)
- Estimating spatial covariance using penalised likelihood with weighted<i>L</i><sub>1</sub>penalty (Q3182743) (← links)
- G-Lasso Network Analysis for Functional Data (Q3300631) (← links)
