Titlebook: Stochastic Population Models; A Compartmental Pers James H. Matis,Thomas R. Kiffe Book 2000 Springer Science+Business Media New York 2000 M

冷漠

Nonlinear Birth-Death Modelsnterpreted as the per-capita birth and death rate coefficients for small initial population sizes, before population density pressures are of any practical consequence. The.are the crowding coefficients which add density-dependency to the model. Their inclusion may in principle yield long-term, equilibrium solutions for the model.

Infant

Linear Immigration-Death-Migration Modelshe case with multiple inputs and two-way migration between compartments. The corresponding deterministic model is given in (8.4) of Chapter 8, with its solution in (8.5) and (8.6), and with the illustration of mercury uptake by fish in Section 8.3.1.

联想

phlegm

Linear Immigration-Death Modelsy in [28] in a compartmental context. A simple application developed subsequently is modeling the bioaccumulation of mercury, described in Section 2.4. We have also used the model extensively to describe the passage of digesta in ruminant animals, see e.g. [15, 16, 59].

向宇宙

0930-0325 It was published as we were busily engaged in modeling African bee dispersal, and provided strong affirmation for the stochastic basis for our ecological modeling efforts. The other is the third edition of Jacquez‘ [28] classic book on compartmental analysis. He reviews stochastic compartmental anal

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上坡

Overview of Modelsthat the wide variety of such models is a natural consequence of the great diversity of the overall objectives for such models. We start by discussing briefly the general modeling objectives upon which this monograph is based.

groggy

Linear Birth-Immigration-Death Models LBID model. Clearly this model with linear (density-independent) growth rates could hold in the case of a.> a.only for periods of initial population growth. The model will be illustrated for such initial population growth for both the African bee and the muskrat examples in Chapter 2.

裹住

Standard Multiple Compartment Analysis with the Deterministic Model[28], leading texts include [3, 22, 85]. As a simple example, the mercury bioaccumulation problem in Section 4.2.2 illustrates the need for a multi-compartment analysis. The techniques have also been applied to ecosystem modeling (see e.g. [52]).

lactic

Basic Methodology for Multiple Population Stochastic Models models. These tools also are considered extensively in the leading texts on applied stochastic processes, including [4, 9, 12, 82]. Jacquez [28] illustrates their use in a standard compartmental context.