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Exploring the Health State of a Population by Dynamic Modeling Methods
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Exploring the Health State of a Population by Dynamic Modeling Methods

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:NT$ 4950 元
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904455
若需訂購本書,請電洽客服 02-25006600[分機130、131]。
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作者簡介

商品簡介

This book introduces and applies the stochastic modeling techniques and the first exit time theory in demography through describing the theory related to the health state of a population and the introduced health state function. The book provides the derivation and classification of the human development stages. The data fitting techniques and related programs are also presented. Many new and old terms are explored and quantitatively estimated, especially the health state or “vitality” of a population, the deterioration and related functions, as well as healthy life expectancy. The book provides the appropriate comparative applications and statistics as connecting tools accompanied by the existing literature, and as such it will be a valuable source to demographers, health scientists, statisticians, economists and sociologists.

作者簡介

Christos H. Skiadas, PhD, was the founder and director of the Data Analysis and Forecasting Laboratory at the Technical University of Crete. He is chair of the Demographics Workshop series, the Applied Stochastic Models and Data Analysis Conference series and the Chaotic Modeling and Simulation Conference series. He has published more than 80 papers, three monographs, and 18 books, including probability, statistics, data analysis and forecasting. His research interests include innovation diffusion modeling and forecasting, life table data modeling, healthy life expectancy estimates, and deterministic, stochastic, and chaotic modeling.

Charilaos Skiadas, PhD, is an associate professor in mathematics and computer science at Hanover College. His research interests encompass a wide array of mathematical and computing topics, ranging from algebraic geometry to statistics and programming languages to data science and health state modeling.

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優惠價:90 4455
若需訂購本書,請電洽客服 02-25006600[分機130、131]。

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