Title: Sequential MCMC methods for controlled branching processes
Authors: Miguel Gonzalez Velasco - University of Extremadura (Spain) [presenting]
Pedro Martin-Chavez - University of Extremadura (Spain)
Ines M del Puerto - University of Extremadura (Spain)
Abstract: Controlled branching processes (CBPs) are stochastic growth population models in which the number of individuals with reproductive capacity in each generation is determined by random control functions. This kind of process is flexible enough to model the evolution of different kinds of populations, including logistic growth populations or epidemic outbreaks (at least in its exponential growth phase). We deal with the estimation of the main parameters of CBPs from a Bayesian perspective. We consider different sampling schemes, including partially observed CBPs. In all situations, we use sequential MCMC methodologies. We show the accuracy of the proposed methodology via simulated examples making use of the statistical software R.