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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 …
explanation for the structure of a data set turn out to have intractable likelihood functions …
Predictive ecology in a changing world
In a rapidly changing world, ecology has the potential to move from empirical and
conceptual stages to application and management issues. It is now possible to make large …
conceptual stages to application and management issues. It is now possible to make large …
[HTML][HTML] Facilitating parameter estimation and sensitivity analysis of agent-based models: A cookbook using NetLogo and R
JC Thiele, W Kurth, V Grimm - Journal of Artificial Societies and Social …, 2014 - jasss.org
Agent-based models are increasingly used to address questions regarding real-world
phenomena and mechanisms; therefore, the calibration of model parameters to certain data …
phenomena and mechanisms; therefore, the calibration of model parameters to certain data …
[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 …
methods which can be implemented without a using likelihood function. In order to use ABC …
Past, present and future of software for Bayesian inference
Software tools for Bayesian inference have undergone rapid evolution in the past three
decades, following popularisation of the first generation MCMC-sampler implementations …
decades, following popularisation of the first generation MCMC-sampler implementations …
Experimental evolution of dispersal: Unifying theory, experiments and natural systems
Dispersal is a central life history trait that affects the ecological and evolutionary dynamics of
populations and communities. The recent use of experimental evolution for the study of …
populations and communities. The recent use of experimental evolution for the study of …
Adaptive approximate Bayesian computation for complex models
We propose a new approximate Bayesian computation (ABC) algorithm that aims at
minimizing the number of model runs for reaching a given quality of the posterior …
minimizing the number of model runs for reaching a given quality of the posterior …
How the spread of user-generated contents (UGC) shapes international tourism distribution: Using agent-based modeling to inform strategic UGC marketing
While user-generated contents (UGC) are recognized as increasingly important to
destination marketing, many DMOs are uncertain how to strategically manage them to their …
destination marketing, many DMOs are uncertain how to strategically manage them to their …
A population data-driven workflow for COVID-19 modeling and learning
CityCOVID is a detailed agent-based model that represents the behaviors and social
interactions of 2.7 million residents of Chicago as they move between and colocate in 1.2 …
interactions of 2.7 million residents of Chicago as they move between and colocate in 1.2 …
Genome-wide signatures of synergistic epistasis during parallel adaptation in a Baltic Sea copepod
The role of epistasis in driving adaptation has remained an unresolved problem dating back
to the Evolutionary Synthesis. In particular, whether epistatic interactions among genes …
to the Evolutionary Synthesis. In particular, whether epistatic interactions among genes …