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Titlebook: Mathematical Modeling in Epidemiology; James C. Frauenthal Textbook 1980 Springer-Verlag Berlin Heidelberg 1980 Epidemiologie.Modeling.bio

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书目名称Mathematical Modeling in Epidemiology
编辑James C. Frauenthal
视频video
丛书名称Universitext
图书封面Titlebook: Mathematical Modeling in Epidemiology;  James C. Frauenthal Textbook 1980 Springer-Verlag Berlin Heidelberg 1980 Epidemiologie.Modeling.bio
描述The text of this book is derived from courses taught by the author in the Department of Applied Mathematics and Statistics at the State University of New York at Stony Brook. The audience for these courses was composed almost entirely of fourth year undergraduate students majoring in the mathematical sciences. The students had ordinarily completed four semesters of calculus and one of probability. Few had any prior experience with differential equations, stochastic processes, or epidemiology. It also seems prudent to mention that the author‘s background is in engineering and applied mathematics and not in epidemiology; it is hoped that this is not painfully obvious. The topics covered in this book have in some cases been modified from the way they were originally presented. However, care has been taken to include a suitable amount of material for a one semester course; the temptation to add gratuitous subject matter has been resisted. Similarly, when a choice between clarity and rigor was available, the more easily understood exposition was selected. By looking only at the table of contents, the casual reader could be easily misled into thinking that the main concern of this book i
出版日期Textbook 1980
关键词Epidemiologie; Modeling; biologisch-mathematisches Modell; epidemiology; linear optimization; mathematica
版次1
doihttps://doi.org/10.1007/978-3-642-67795-3
isbn_softcover978-3-540-10328-8
isbn_ebook978-3-642-67795-3Series ISSN 0172-5939 Series E-ISSN 2191-6675
issn_series 0172-5939
copyrightSpringer-Verlag Berlin Heidelberg 1980
The information of publication is updating

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James C. Frauenthalt from the one predicted by PDEs and ODEs. The total population of the agents increases indefinitely in situations where the classical lore predicted a decreasing population. We analyze the behavior of these systems using a renormalization group analysis to show that the discrete distribution of the
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James C. Frauenthalcribing the histogram of earthquakes of a given strength; (ii) for a wide range of economic organizations, the histogram that shows how size of organization is inversely correlated to fluctuations in size with an exponent ≈ 0.2. Neither of these two new empirical laws has a firm theoretical foundati
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James C. Frauenthalcribing the histogram of earthquakes of a given strength; (ii) for a wide range of economic organizations, the histogram that shows how size of organization is inversely correlated to fluctuations in size with an exponent ≈ 0.2. Neither of these two new empirical laws has a firm theoretical foundati
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ce lipid layer. We presented these surface receptors with antigen with varying concentration and valence. Using experimentally reasonable values for the binding and unbinding probabilities for the binding sites on the antigens, we simulated the dynamics of the binding process. Using the single hypot
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