Likelihood Ratio Tests for a Large Directed Acyclic Graph
From MaRDI portal
Publication:5120668
DOI10.1080/01621459.2019.1623042zbMath1441.62249OpenAlexW2945624329WikidataQ99711079 ScholiaQ99711079MaRDI QIDQ5120668
Xiaotong Shen, Wei Pan, Chunlin Li
Publication date: 15 September 2020
Published in: Journal of the American Statistical Association (Search for Journal in Brave)
Full work available at URL: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7508303
Inference from spatial processes (62M30) Applications of statistics to biology and medical sciences; meta analysis (62P10)
Related Items
Classified generalized linear mixed model prediction incorporating pseudo‐prior information, Pseudo-Bayesian Classified Mixed Model Prediction, Estimation of Gaussian directed acyclic graphs using partial ordering information with applications to DREAM3 networks and dairy cattle data
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
- Penalized Estimation of Directed Acyclic Graphs From Discrete Data
- Causal inference using invariant prediction: identification and confidence intervals
- CAM: causal additive models, high-dimensional order search and penalized regression
- Bayesian hierarchical modeling for signaling pathway inference from single cell interventional data
- How close is the sample covariance matrix to the actual covariance matrix?
- A central limit theorem under metric entropy with \(L_ 2\) bracketing
- Learning Bayesian networks from data: An information-theory based approach
- The DC (Difference of convex functions) programming and DCA revisited with DC models of real world nonconvex optimization problems
- A deterministic algorithm for global optimization
- Adaptive estimation of a quadratic functional by model selection.
- On the asymptotics of constrained \(M\)-estimation
- Probability inequalities for likelihood ratios and convergence rates of sieve MLEs
- Causal Dantzig: fast inference in linear structural equation models with hidden variables under additive interventions
- Variational Analysis
- Likelihood-Based Selection and Sharp Parameter Estimation
- Learning Sparse Causal Gaussian Networks With Experimental Intervention: Regularization and Coordinate Descent
- Identifiability of Gaussian structural equation models with equal error variances
- Constrained likelihood for reconstructing a directed acyclic Gaussian graph
- Monte Carlo strategies in scientific computing
