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.
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.
Lyle D. Broemeling, Ph.D., is Director of Broemeling and Associates Inc., and is a consulting biostatistician. He has been involved with academic health science centers for about 20 years and has taught and been a consultant at the University of Texas Medical Branch in Galveston, the University of Texas MD Anderson Cancer Center and the University of Texas School of Public Health. His main interest is in developing Bayesian methods for use in medical and biological problems and in authoring textbooks in statistics. His previous books are Bayesian Biostatistics and Diagnostic Medicine, and Bayesian Methods for Agreement.
Inhaltsangabe
Contents Author ......................................................................................iv 1. Introduction to Bayesian Inferences for Infectious Diseases ..................1 2. Bayesian Analysis ...........................................................................................5 3. Infectious Diseases .................................................................................. .....39 4. Bayesian Inference for Discrete Markov Chains: Their Relevance to Infectious Diseases .....................................................59 5. Biological Examples Modeled by Discrete Markov Chains................ 113 6. Inferences for Markov Chains in Continuous Time .............................149 7. Bayesian Inference: Biological Processes that Follow a Continuous Time Markov Chain ...........................................................195 8. Additional Information about Infectious Diseases ..............................253 Index ..................................................................................................... 315
Contents Author ......................................................................................iv 1. Introduction to Bayesian Inferences for Infectious Diseases ..................1 2. Bayesian Analysis ...........................................................................................5 3. Infectious Diseases .................................................................................. .....39 4. Bayesian Inference for Discrete Markov Chains: Their Relevance to Infectious Diseases .....................................................59 5. Biological Examples Modeled by Discrete Markov Chains................ 113 6. Inferences for Markov Chains in Continuous Time .............................149 7. Bayesian Inference: Biological Processes that Follow a Continuous Time Markov Chain ...........................................................195 8. Additional Information about Infectious Diseases ..............................253 Index ..................................................................................................... 315
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