Stochastic models in population biology: from dynamic noise to Bayesian description and model comparison for given data sets

DOI10.1080/00207160.2013.792924zbMath1291.92011OpenAlexW2034123708WikidataQ62045051 ScholiaQ62045051MaRDI QIDQ5416459

Luís Mateus, Jean-Claude Zambrini, Nico Stollenwerk

Publication date: 20 May 2014

Published in: International Journal of Computer Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207160.2013.792924

zbMATH Keywords

Bayes factorPoisson processMarkov processes in continuous timelinear infection model

Mathematics Subject Classification ID

Bayesian inference (62F15) Markov processes: estimation; hidden Markov models (62M05) Dynamical systems and their relations with probability theory and stochastic processes (37A50) Markov processes: hypothesis testing (62M02) General biology and biomathematics (92B05)

Related Items

Sensitivity analysis and variance reduction in a stochastic non-destructive testing problem ⋮ Prediction and Predictability in Population Biology: Noise and Chaos ⋮ Epidemiological models in semiclassical approximation: an analytically solvable model as a test case

Cites Work

• The role of seasonality and import in a minimalistic multi-strain dengue model capturing differences between primary and secondary infections: complex dynamics and its implications for data analysis
• Epidemiology of Dengue Fever: A Model with Temporary Cross-Immunity and Possible Secondary Infection Shows Bifurcations and Chaotic Behaviour in Wide Parameter Regions
• Torus bifurcations, isolas and chaotic attractors in a simple dengue fever model with ADE and temporary cross immunity
• Unnamed Item
• Unnamed Item