Proposes adaptive multiple importance sampling for robust Bayesian model evidence estimation under parameter non-identifiability, shown to outperform deterministic methods on ecological case studies while being cheaper than MCMC.
On structural and practical identifiability
6 Pith papers cite this work. Polarity classification is still indexing.
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Introduces local information operators that separate pointwise visibility from spatial identifiability via linearized Fisher information and sensitivity Gramians in distributed-parameter inverse problems.
Trajectory data resolves structural non-identifiability in lattice random walk diffusion models that count data alone cannot, with analysis of experimental design impacts on practical identifiability.
Modeling three labels in five-label lipid metabolism experiments balances parameter estimation accuracy, trajectory recovery, and computational cost better than using one or all labels.
Simulation study finds 5-state multistate models for MCED data perform similarly to 3-state models in robustness while 9-state models lose identifiability and precision, with hierarchical models and informative priors offering partial improvements.
A tutorial on using StructuralIdentifiability.jl to assess local and global identifiability in ODE models with examples from epidemiology, pharmacokinetics, and systems biology.
citing papers explorer
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Reliable model selection in the presence of parameter non-identifiability
Proposes adaptive multiple importance sampling for robust Bayesian model evidence estimation under parameter non-identifiability, shown to outperform deterministic methods on ecological case studies while being cheaper than MCMC.
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Local Information Operators for Spatial Identifiability in Distributed-Parameter Inverse Problems in Computational Mechanics
Introduces local information operators that separate pointwise visibility from spatial identifiability via linearized Fisher information and sensitivity Gramians in distributed-parameter inverse problems.
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When do trajectories matter? Identifiability analysis for stochastic transport phenomena
Trajectory data resolves structural non-identifiability in lattice random walk diffusion models that count data alone cannot, with analysis of experimental design impacts on practical identifiability.
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Balancing label resolution and computational cost in dynamical models of lipid metabolism
Modeling three labels in five-label lipid metabolism experiments balances parameter estimation accuracy, trajectory recovery, and computational cost better than using one or all labels.
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Modelling multi-cancer screening data to infer on natural history of disease: when can valid, identifiable and precise inference be obtained?
Simulation study finds 5-state multistate models for MCED data perform similarly to 3-state models in robustness while 9-state models lose identifiability and precision, with hierarchical models and informative priors offering partial improvements.
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A Tutorial on Symbolic Structural Identifiability Analysis of ODE Models in Julia
A tutorial on using StructuralIdentifiability.jl to assess local and global identifiability in ODE models with examples from epidemiology, pharmacokinetics, and systems biology.