Derives heuristic coverage bounds for MLFriends nested sampling under a Binomial point process model, claiming the bias is negligible compared to statistical variance.
arXiv e- prints, 2005–08602 (2020) arXiv:2005.08602 [math.ST]
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A trans-dimensional Bayesian model set averaging framework for 13C-MFA that averages flux estimates over uncertain network topologies using reversible jump MCMC and diffusive nested sampling.
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First analytical coverage bounds of a fully specified nested sampling algorithm
Derives heuristic coverage bounds for MLFriends nested sampling under a Binomial point process model, claiming the bias is negligible compared to statistical variance.
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Trans-dimensional Bayesian model averaging for $^{13}$C-based metabolic flux analysis: Evidence-based flux inference under structural model uncertainty
A trans-dimensional Bayesian model set averaging framework for 13C-MFA that averages flux estimates over uncertain network topologies using reversible jump MCMC and diffusive nested sampling.