Pages that link to "Item:Q3434147"
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The following pages link to Gradient directed regularization for sparse Gaussian concentration graphs, with applications to inference of genetic networks (Q3434147):
Displaying 34 items.
- A sparse conditional Gaussian graphical model for analysis of genetical genomics data (Q80801) (← links)
- Sparse factor model for co-expression networks with an application using prior biological knowledge (Q306641) (← links)
- Learning local directed acyclic graphs based on multivariate time series data (Q386754) (← links)
- Adjusting for high-dimensional covariates in sparse precision matrix estimation by \(\ell_1\)-penalization (Q391559) (← links)
- Model selection and estimation in the matrix normal graphical model (Q413758) (← links)
- Multiple testing and error control in Gaussian graphical model selection (Q449776) (← links)
- Shrinkage tuning parameter selection in precision matrices estimation (Q538141) (← links)
- Regularized rank-based estimation of high-dimensional nonparanormal graphical models (Q741796) (← links)
- Estimating heterogeneous graphical models for discrete data with an application to roll call voting (Q746672) (← links)
- An efficient algorithm for sparse inverse covariance matrix estimation based on dual formulation (Q1796959) (← links)
- Estimating networks with jumps (Q1950892) (← links)
- Bootstrap inference for network construction with an application to a breast cancer microarray study (Q1951540) (← links)
- Network modeling in biology: statistical methods for gene and brain networks (Q2038287) (← links)
- Sparse estimation of high-dimensional inverse covariance matrices with explicit eigenvalue constraints (Q2059164) (← links)
- Review on statistical methods for gene network reconstruction using expression data (Q2260287) (← links)
- Network exploration via the adaptive LASSO and SCAD penalties (Q2270657) (← links)
- Node-structured integrative Gaussian graphical model guided by pathway information (Q2405417) (← links)
- Confidence intervals for heritability via Haseman-Elston regression (Q2406191) (← links)
- Universal construction mechanism for networks from one-dimensional symbol sequences (Q2449208) (← links)
- Learning Oncogenic Pathways from Binary Genomic Instability Data (Q3008875) (← links)
- Regularized Parameter Estimation in High-Dimensional Gaussian Mixture Models (Q3016190) (← links)
- Variable selection and dependency networks for genomewide data (Q3304982) (← links)
- An efficient method for identifying statistical interactors in gene association networks (Q3304992) (← links)
- A Localization Approach to Improve Iterative Proportional Scaling in Gaussian Graphical Models (Q3585266) (← links)
- Robust Gaussian Graphical Modeling Via <i>l</i><sub>1</sub> Penalization (Q4911945) (← links)
- Likelihood-Based Selection and Sharp Parameter Estimation (Q4916454) (← links)
- An Efficient Linearly Convergent Regularized Proximal Point Algorithm for Fused Multiple Graphical Lasso Problems (Q4999369) (← links)
- A Proximal Point Dual Newton Algorithm for Solving Group Graphical Lasso Problems (Q5116554) (← links)
- MARS as an alternative approach of Gaussian graphical model for biochemical networks (Q5138750) (← links)
- Effectiveness of combinations of Gaussian graphical models for model building (Q5218890) (← links)
- A computationally fast alternative to cross-validation in penalized Gaussian graphical models (Q5220930) (← links)
- Assessment of Covariance Selection Methods in High-Dimensional Gaussian Graphical Models (Q6066549) (← links)
- Comparing dependent undirected Gaussian networks (Q6122076) (← links)
- Monitoring Heterogeneous Multivariate Profiles Based on Heterogeneous Graphical Model (Q6631062) (← links)
