Bayesian estimation of the offspring mean in branching processes: application to infectious disease data

DOI10.1016/j.camwa.2012.01.049zbMath1252.62084OpenAlexW2034484284MaRDI QIDQ692242

Angel G. Angelov, Maroussia Slavtchova-Bojkova

Publication date: 4 December 2012

Published in: Computers \& Mathematics with Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.camwa.2012.01.049

zbMATH Keywords

Metropolis-Hastings algorithmreproduction numberBienaymé-Galton-Watson branching process

Mathematics Subject Classification ID

Epidemiology (92D30) Bayesian inference (62F15) Markov processes: estimation; hidden Markov models (62M05) Applications of branching processes (60J85)

Related Items (5)

The challenges of modeling and forecasting the spread of COVID-19 ⋮ Robust estimation in controlled branching processes: Bayesian estimators via disparities ⋮ Stochastic monotonicity and continuity properties of functions defined on Crump-Mode-Jagers branching processes, with application to vaccination in epidemic modelling ⋮ Second order longitudinal dynamic models with covariates: estimation and forecasting ⋮ Parameter estimation for the fractional fractal diffusion model based on its numerical solution

Uses Software

• R
• CODA

Cites Work

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• ON ASSESSING THE POTENTIAL SEVERITY OF AN OUTBREAK OF A RARE INFECTIOUS DISEASE: A BAYESIAN APPROACH
• On parametric estimation for mortal branching processes
• Decision—theoretic estimation of the offspring mean in mortal branching processes
• The concept of R_o in epidemic theory
• The distribution of time to extinction in subcritical branching processes: applications to outbreaks of infectious disease
• The Bayesian Choice
• Branching process models for surveillance of infectious diseases controlled by mass vaccination
• The Borel-Tanner distribution
• Introducing Monte Carlo Methods with R

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