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A central limit theorem for age- and density-dependent population processes
Authors:Frank JS Wang
Institution:Department of Mathematics, University of Montana, Missoula, Montana 59801, U.S.A.
Abstract:Consider a population consisting of one type of individual living in a fixed region with area A. In 8], we constructed a stochastic population model in which the death rate is affected by the age of the individual and the birth rate is affected by the population density PA(t), i.e., the population size divided by the area A of the given region. In 8], we proposed a continuous deterministic model which in general is a nonlinear Volterra type integral equation and proved that under appropriate conditions the sequence PA(t) would converge to the solution P(t) of our integral equation in the sense that
lim→∞Psup0?s?t|PA(s) ? P(s)|>ε=0 for every ε > 0
.In this paper, we obtain a “central limit theorem” for the random element √A(PA(t)?P(t)). We prove that under appropriate conditions √A(PA(t)?P(t)) will converge to a Gaussian process. (See Theorem 3.4 for the explicit formula of this Gaussian process.)
Keywords:Primary 92A15  60K99  Secondary 60F05  population process  Gaussaian process  Skorohod topology  partial differential  central limit theorem  resolvent kernel  tightness
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