5 citations · 5 across the 1 of their papers we have counts for
5 papers
Invariant Image Reparameterisation: Bridging Symbolic and Numerical Methods for Identifiability Analysis, Model Reduction, and Prediction
Oliver J. Maclaren, Ruanui Nicholson, Joel A. Trent +2
Structural and practical parameter non-identifiability issues are common when mathematical models are used to interpret data. Such issues motivate model reparameterisation and redu…
Parameter Estimation for Differential Equation Models Using Generalized Profiling: A Computational Tutorial
Matthew J Simpson, James S Bennett, Alexander Johnston +1
Parameter estimation connects mathematical models to real-world data and decision making across many scientific and industrial applications. Standard approaches such as maximum lik…
A generalised sigmoid population growth model with energy dependence: application to quantify the tipping point for Antarctic shallow seabed algae
Elise Mills, Graeme F. Clark, Matthew J. Simpson +2
Sigmoid growth models are often used to study population dynamics. The size of a population at equilibrium commonly depends explicitly on the availability of resources, such as an…
Parameter identifiability, parameter estimation and model prediction for differential equation models
Matthew J Simpson, Ruth E Baker
Interpreting data with mathematical models is an important aspect of real-world industrial and applied mathematical modeling. Often we are interested to understand the extent to wh…
Efficient inference for differential equation models without numerical solvers
Alexander Johnston, Ruth E. Baker, Matthew J. Simpson
Parameter inference is essential when interpreting observational data using mathematical models. Standard inference methods for differential equation models typically rely on obtai…