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Mathematical Demography: Theory and Modeling
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Mathematical Demography: Theory and Modeling

Book Details

Format Paperback / Softback
ISBN-10 9819561280
ISBN-13 9789819561285
Publisher Springer Verlag, Singapore
Imprint Springer Verlag, Singapore
Country of Manufacture GB
Country of Publication GB
Publication Date May 29th, 2026
Print length 173 Pages
Weight 304 grams
Dimensions 23.20 x 15.50 x 1.50 cms
Ksh 9,900.00
Publisher Out of Stock 0 in stock

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This textbook is written with the intention of providing the essentials of foundational training in modeling, both mathematical and stochastic. Partial differential equations models of single population dynamics, McKendrick von Foerster models of population growth and Okubo’s diffusion models are derived.
This textbook is written with the intention of providing the essentials of foundational training in modeling, both mathematical and stochastic. It offers a comprehensive understanding of theoretical and formal mathematical demography and human population dynamics. Presented in an engaging, clear and concise manner, it aims to outline traditional material and recent advancements in the field, specifically tailored for both beginners and professionals. Separate chapters discuss classical as well as recent developments in stable and stationary populations, such as Euler–Lotka population equations, and life tables. Partial differential equations models of single population dynamics, McKendrick von Foerster models of population growth and Okubo’s diffusion models are derived. Population ecology models like the Lotka–Volterra two-population framework, Kermack–McKendrick three-population models, and their stability analysis foundations are succinctly explained. Recent advancements in stationary population theories and newer population stability principles developed are included. The book also includes two chapters on stochastic process models in demography. The content of the book is not only accessible and relevant to students and researchers in mathematical demography but also to those working in actuarial science, ecology, statistics and mathematical modeling.

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