What question did this study set out to answer?

The aim is to develop a Bayesian optimal design for experiments involving nonlinear ordinary differential equations related to amino acid transport in placentas.

May 17, 2019Journal of the American Statistical AssociationOpen Access

Bayesian Optimal Design for Ordinary Differential Equation Models With Application in Biological Science

View Full Paper

Ask AI

Bookmark

Authors

AOAntony M. OverstallUniversity of Southampton DWDavid C. WoodsUniversity of Southampton BPBen M. ParkerBrunel University of London

Discussion

Member takes

Implication

Randomized trial demonstrates improved parameter estimation in biological models, highlighting computational feasibility.

Key Points

The aim is to develop a Bayesian optimal design for experiments involving nonlinear ordinary differential equations related to amino acid transport in placentas.
Introduces a probabilistic solution to nonlinear differential equations combined with Monte Carlo approximation.
Utilizes cyclic descent for optimizing the design while addressing computational challenges.
Presents a novel precomputation algorithm to ease the solution process for complex models.
Achieves optimal designs for typical models derived from differential equations, enhancing experimental efficiency.
Implements successful designs specifically for the placenta experiment, increasing accuracy in parameter estimation.

Cite This Study

Overstall et al. (2019) studied this question.

synapsesocial.com/papers/6a15419337103a43379f7464 https://doi.org/10.1080/01621459.2019.1617154

View Full Paper

Ask AI

Bookmark

Bayesian Optimal Design for Ordinary Differential Equation Models With Application in Biological Science

Discussion

Member takes

Implication

Key Points

Cite This Study

Bayesian Optimal Design for Ordinary Differential Equation Models With Application in Biological Science

Discussion

Member takes

Implication

Key Points

Cite This Study

Also Consider

Also Consider