Formalizes pre-data effective sample size for GGMs under Wishart and G-Wishart priors and introduces DPIR and BFDA extensions for sample size planning.
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3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
years
2026 3verdicts
UNVERDICTED 3representative citing papers
An information-theoretic multiplex hypergraph model quantifies synergistic and redundant higher-order interactions in eating disorder psychometric networks, identifying a stable transdiagnostic core and diagnosis-specific combinations.
Modifies Gibbs sampler for GP state-space models, introduces CFA measurement structure, and validates software via simulation-based calibration to enable reliable learning of nonlinear latent dynamics.
citing papers explorer
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What is your Prior Worth? Effective Sample Size and Sample Size Planning for Gaussian Graphical Models
Formalizes pre-data effective sample size for GGMs under Wishart and G-Wishart priors and introduces DPIR and BFDA extensions for sample size planning.
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Multiplex Hypergraph Modeling of Higher Order Structures in Psychometric Networks
An information-theoretic multiplex hypergraph model quantifies synergistic and redundant higher-order interactions in eating disorder psychometric networks, identifying a stable transdiagnostic core and diagnosis-specific combinations.
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Learning Nonlinear Dynamics: Improving the Estimation Efficiency and Reliability of Gaussian Process State-Space Models
Modifies Gibbs sampler for GP state-space models, introduces CFA measurement structure, and validates software via simulation-based calibration to enable reliable learning of nonlinear latent dynamics.