Name: Bayesian Analysis of Infectious Diseases: Covid-19 and Beyond (Chapman & Hall (en Inglés)
Price: 114080.00 CLP
Availability: InStock
Author: Lyle D. Broemeling
ISBN: 9780367633868

portada Bayesian Analysis of Infectious Diseases: Covid-19 and Beyond (Chapman & Hall (en Inglés)

Formato

Libro Físico

Autor

Lyle D. Broemeling

Año

2021

Idioma

Inglés

N° páginas

342

Encuadernación

Tapa Dura

ISBN13

9780367633868

N° edición

Categorías

Inferencia bayesiana

Bayesian Analysis of Infectious Diseases: Covid-19 and Beyond (Chapman & Hall (en Inglés)

Lyle D. Broemeling (Autor) · · Tapa Dura

Libro Nuevo

$ 114.080

$ 228.150

Ahorras: $ 114.070

50% descuento

Envío normal

Origen: Estados Unidos (Costos de importación incluídos en el precio)

Se enviará desde nuestra bodega entre el Martes 11 de Junio y el Martes 25 de Junio.

Lo recibirás en cualquier lugar de Chile entre 1 y 3 días hábiles luego del envío.

Reseña del libro "Bayesian Analysis of Infectious Diseases: Covid-19 and Beyond (Chapman & Hall (en Inglés)"

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.