Approximate bayesian computation

MA Beaumont - Annual review of statistics and its application, 2019 - annualreviews.org
Many of the statistical models that could provide an accurate, interesting, and testable
explanation for the structure of a data set turn out to have intractable likelihood functions …

Analyzing stochastic computer models: A review with opportunities

E Baker, P Barbillon, A Fadikar, RB Gramacy… - Statistical …, 2022 - projecteuclid.org
Analyzing Stochastic Computer Models: A Review with Opportunities Page 1 Statistical
Science 2022, Vol. 37, No. 1, 64–89 https://doi.org/10.1214/21-STS822 © Institute of …

[HTML][HTML] Approximate Bayesian Computation for infectious disease modelling

A Minter, R Retkute - Epidemics, 2019 - Elsevier
Abstract Approximate Bayesian Computation (ABC) techniques are a suite of model fitting
methods which can be implemented without a using likelihood function. In order to use ABC …

Challenges in estimation, uncertainty quantification and elicitation for pandemic modelling

B Swallow, P Birrell, J Blake, M Burgman, P Challenor… - Epidemics, 2022 - Elsevier
The estimation of parameters and model structure for informing infectious disease response
has become a focal point of the recent pandemic. However, it has also highlighted a …

June: open-source individual-based epidemiology simulation

J Aylett-Bullock, C Cuesta-Lazaro… - Royal Society …, 2021 - royalsocietypublishing.org
We introduce June, an open-source framework for the detailed simulation of epidemics on
the basis of social interactions in a virtual population constructed from geographically …

Bayesian emulation and history matching of JUNE

I Vernon, J Owen, J Aylett-Bullock… - … of the Royal …, 2022 - royalsocietypublishing.org
We analyze JUNE: a detailed model of COVID-19 transmission with high spatial and
demographic resolution, developed as part of the RAMP initiative. JUNE requires substantial …

A quantitative systems pharmacology perspective on the importance of parameter identifiability

A Sher, SA Niederer, GR Mirams… - Bulletin of Mathematical …, 2022 - Springer
There is an inherent tension in Quantitative Systems Pharmacology (QSP) between the
need to incorporate mathematical descriptions of complex physiology and drug targets with …

Calibration of individual-based models to epidemiological data: A systematic review

CM Hazelbag, J Dushoff, EM Dominic… - PLoS computational …, 2020 - journals.plos.org
Individual-based models (IBMs) informing public health policy should be calibrated to data
and provide estimates of uncertainty. Two main components of model-calibration methods …

Bayesian uncertainty analysis for complex systems biology models: emulation, global parameter searches and evaluation of gene functions

I Vernon, J Liu, M Goldstein, J Rowe, J Topping… - BMC systems …, 2018 - Springer
Background Many mathematical models have now been employed across every area of
systems biology. These models increasingly involve large numbers of unknown parameters …

Urban land-use planning under multi-uncertainty and multiobjective considering ecosystem service value and economic benefit-A case study of Guangzhou, China

PP Gao, YP Li, JW Gong, GH Huang - Ecological Complexity, 2021 - Elsevier
Effective land-use planning considering ecosystem service value (ESV) is indispensable in
facilitating economic development and eco-environment sustainability. In this study, a Monte …