2 citations · 3 across the 10 of their papers we have counts for
4 papers · 1 filter
Reliable model selection in the presence of parameter non-identifiability
Yong See Foo, Torkel E. Loman, Alexander P. Browning +3
Mathematical models are invaluable for understanding and predicting how biological systems behave, although their construction requires specifying mechanisms and relationships that…
Structural identifiability of partially-observed stochastic processes: from single-particle trajectories to total particle density data
Arianna Ceccarelli, Alexander P. Browning, Ruth E. Baker
The increasing availability of experimental data has intensified interest in calibrating stochastic models, raising fundamental questions about parameter identifiability. Structura…
A likelihood-based Bayesian inference framework for the calibration of and selection between stochastic velocity-jump models
Arianna Ceccarelli, Alexander P. Browning, Tai Chaiamarit +2
Advances in experimental techniques allow the collection of high-resolution spatio-temporal data that track individual motile entities. These tracking data can be used to calibrate…
Exact identifiability analysis for a class of partially observed near-linear stochastic differential equation models
Alexander P Browning, Michael J Chappell, Hamid Rahkooy +2
Stochasticity plays a key role in many biological systems, necessitating the calibration of stochastic mathematical models to interpret associated data. For model parameters to be…