Stochastic Model for Population Data Using a Birth–Death Diffusion Growth Rate Process
One of the important functions of the demographer is to provide information on the future population which is important to plan for human activities. There is a
considerable interest in stochastic analogs of classical differences and differential equations describing phenomena in theoretical models involving population data structure. In this paper a description of population data using a solution of stochastic differential equation is considered. More specifically, the
population data process follows a Geometric progression with growth rate follow a birth and death diffusion process is studied. The mean and the variance approximation as well as the sample path of such a process are also obtained. The model is applied to the USA male population from 1900 to 1999 based on agespecific death rates per 100,000 populations in specified group computed by the direct method (Donna et al., 2001). The results clearly demonstrated the appropriateness of the predicted model.