Stochastic Population Models: A Compartmental Perspective / Edition 1

Stochastic Population Models: A Compartmental Perspective / Edition 1

ISBN-10:
038798657X
ISBN-13:
9780387986579
Pub. Date:
06/15/2000
Publisher:
Springer New York
ISBN-10:
038798657X
ISBN-13:
9780387986579
Pub. Date:
06/15/2000
Publisher:
Springer New York
Stochastic Population Models: A Compartmental Perspective / Edition 1

Stochastic Population Models: A Compartmental Perspective / Edition 1

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Overview

The book focuses on shastic modeling of population processes. The book presents new symbolic mathematical software to develop practical methodological tools for shastic population modeling. The book assumes calculus and some knowledge of mathematical modeling, including the use of differential equations and matrix algebra.


Product Details

ISBN-13: 9780387986579
Publisher: Springer New York
Publication date: 06/15/2000
Series: Lecture Notes in Statistics Series , #145
Edition description: Softcover reprint of the original 1st ed. 2000
Pages: 202
Product dimensions: 6.10(w) x 9.25(h) x 0.02(d)

Table of Contents

I Introduction.- 1. Overview of Models.- 1.1 Modeling Objectives.- 1.2 Structure of Monograph.- 2. Some Applications.- 2.1 Introduction.- 2.2 Application to Invasion of Africanized Honey Bee.- 2.3 Application to Muskrat Spread in the Netherlands.- 2.4 Application to Bioaccumulation of Mercury in Fish.- 2.5 Application to Human Calcium Kinetics.- II Models for a Single Population.- 3. Basic Methodology for Single Population Shastic Models.- 3.1 Introduction.- 3.2 Basic Assumptions.- 3.3 Moments and Cumulants.- 3.4 Kolmogorov Differential Equations.- 3.5 Generating Functions.- 3.6 Partial Differential Equations for Generating Functions.- 3.7 General Approach to Single Population Growth Models.- 4. Linear Immigration-Death Models.- 4.1 Introduction.- 4.2 Deterministic Model.- 4.3 Probability Distributions for the Shastic Model.- 4.4 Generating Functions.- 4.5 Cumulant Functions.- 4.6 Some Properties of the Shastic Solution.- 4.7 Illustrations.- 5. Linear Birth-Immigration-Death Models.- 5.1 Introduction.- 5.2 Deterministic Model.- 5.3 Probability Distribution for the Shastic Model.- 5.4 Generating Functions.- 5.5 Cumulant Functions.- 5.6 Some Properties of the Shastic Solution.- 5.7 Illustrations.- 6. Nonlinear Birth-Death Models.- 6.1 Introduction.- 6.2 Deterministic Model.- 6.3 Probability Distributions for the Shastic Model.- 6.4 Generating Functions.- 6.5 Cumulant Functions.- 6.6 Some Properties of the Shastic Solution.- 6.7 Illustrations.- 6.8 Appendices.- III Models for Multiple Populations.- 7. Nonlinear Birth-Immigration-Death Models.- 7.1 Introduction.- 7.2 Deterministic Model.- 7.3 Probability Distribution for the Shastic Model.- 7.4 Generating Functions.- 7.5 Cumulant Functions.- 7.6 Some Properties of the Shastic Solution.- 7.7 Illustrations.- 7.8 Appendices.- 8. Standard Multiple Compartment Analysis.- 8.1 Introduction.- 8.2 Deterministic Model Formulation and Solution.- 8.3 Illustrations.- 9. Basic Methodology for Multiple Population Shastic Models.- 9.1 Introduction.- 9.2 Basic Assumptions.- 9.3 Joint Moments and Cumulants.- 9.4 Kolmogorov Differential Equations.- 9.5 Bivariate Generating Functions.- 9.6 Partial Differential Equations for Generating Functions.- 9.7 General Approach to Multiple Population Growth Models.- 10. Linear Death-Migration Models.- 10.1 Introduction.- 10.2 General Formulation of the Shastic Model.- 10.3 Direct Solution for Shastic Migration-Death Model.- 10.4 Mean Residence Times.- 10.5 Appendix.- 11. Linear Immigration-Death-Migration Models.- 11.1 Introduction.- 11.2 Generating Functions for the Shastic Model.- 11.3 Probability Distribution.- 11.4 Cumulant Functions.- 12. Linear Birth-Immigration-Death-Migration Models.- 12.1 Introduction.- 12.2 Equations for Cumulant Functions.- 12.3 Application to Dispersal of African Bees-Basic Model.- 12.4 Application to Muskrat Spread Data.- 12.5 Appendix.- 13. Nonlinear Birth-Death-Migration Models.- 13.1 Introduction.- 13.2 Probability Distribution for the Shastic Model.- 13.3 Cumulant Functions.- 14. Nonlinear Host-Parasite Models.- 14.1 Introduction.- 14.2 Proposed Host-Parasite Model.- 14.3 Conclusions and Future Research Directions.- 14.4 Appendix.- References.

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