Estimation of growth rate in second order branching process
Abstract
The classical Bienayme-Galton-Watson (BGW) branching process assumes first order dependence, whereas many real life datasets exhibit a second or higher order dependence.
Further, in some situations, there is a need for a model which allows for simultaneous reproduction by a parent and its offspring.
In this talk, we present a second order BGW (SOBGW) model to deal with such situations.
Further we discuss estimation of growth rate for SOBGW model when only the generation sizes are observed.
This model is further used to model the swine flu data for Pune, India and La-Gloria, Mexico.