Bayesian analysis of infectious diseases COVID-19 and beyond / [electronic resource]:

• 作者： Broemeling, Lyle D., 1939- author.
• 其他題名：
  • Chapman & Hall/CRC biostatistics series.
• 出版： Boca Raton : CRC Press
• 叢書名： Chapman & Hall/CRC biostatistics series
• 主題： Communicable diseases--Statistics. , Bayesian statistical decision theory. , Disease Transmission, Infectious--statistics & numerical data , Maladies infectieuses--Statistiques. , Theorie de la decision bayesienne. , MATHEMATICS / Probability & Statistics / Bayesian Analysis , MEDICAL / Biostatistics , MEDICAL / Infectious Diseases , Bayesian statistical decision theory. , Communicable diseases. , Statistics.
• ISBN： 9781003125983 (electronic bk.) 、 1003125980 (electronic bk.) 、 9781000336474 (electronic bk.) 、 1000336476 (electronic bk.) 、 9781000336313 (electronic bk.) 、 100033631X (electronic bk.)
• FIND@SFXID: CGU
• 資料類型: 電子書
• 內容註: Contents--Author iv...1. Introduction to Bayesian Inferences for Infectious Diseases..................12. Bayesian Analysis -- 53. Infectious Diseases ........394. Bayesian Inference for Discrete Markov Chains:Their Relevance to Infectious Diseases.........595. Biological Examples Modeled by Discrete Markov Chains................ 1136. Inferences for Markov Chains in Continuous Time.........1497. Bayesian Inference: Biological Processes that Follow a Continuous Time Markov Chain.......1958. Additional Information about Infectious Diseases.......253Index ...... 315 Includes bibliographical references and index.
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• 摘要註: Bayesian Analysis of Infectious Diseases -COVID-19 and Beyond shows how the Bayesian approach can be used to analyze the evolutionary behavior of infectious diseases, including the coronavirus pandemic. The book describes the foundation of Bayesian statistics while explicating the biology and evolutionary behavior of infectious diseases, including viral and bacterial manifestations of the contagion. The book discusses the application of Markov Chains to contagious diseases, previews data analysis models, the epidemic threshold theorem, and basic properties of the infection process. Also described are the chain binomial model for the evolution of epidemics. Features: Represents the first book on infectious disease from a Bayesian perspective. Employs WinBUGS and R to generate observations that follow the course of contagious maladies. Includes discussion of the coronavirus pandemic as well as many examples from the past, including the flu epidemic of 1918-1919. Compares standard non-Bayesian and Bayesian inferences. Offers a companion website with the R and WinBUGS code.
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