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Likelihood and Bayesian inference = ...

Held, Leonhard.

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Likelihood and Bayesian inference = with applications in biology and medicine /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Likelihood and Bayesian inference/ by Leonhard Held, Daniel Sabanes Bove.
其他題名:	with applications in biology and medicine /
作者:	Held, Leonhard.
其他作者:	Sabanes Bove, Daniel.
出版者:	Berlin, Heidelberg :Springer Berlin Heidelberg : : 2020.,
面頁冊數:	xiii, 402 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Bayesian statistical decision theory. -
電子資源:	https://doi.org/10.1007/978-3-662-60792-3
ISBN:	9783662607923

Likelihood and Bayesian inference = with applications in biology and medicine /
Held, Leonhard.

Likelihood and Bayesian inferencewith applications in biology and medicine /[electronic resource] :by Leonhard Held, Daniel Sabanes Bove. - Second edition. - Berlin, Heidelberg :Springer Berlin Heidelberg :2020. - xiii, 402 p. :ill., digital ;24 cm. - Statistics for biology and health,1431-8776. - Statistics for biology and health..

This richly illustrated textbook covers modern statistical methods with applications in medicine, epidemiology and biology. Firstly, it discusses the importance of statistical models in applied quantitative research and the central role of the likelihood function, describing likelihood-based inference from a frequentist viewpoint, and exploring the properties of the maximum likelihood estimate, the score function, the likelihood ratio and the Wald statistic. In the second part of the book, likelihood is combined with prior information to perform Bayesian inference. Topics include Bayesian updating, conjugate and reference priors, Bayesian point and interval estimates, Bayesian asymptotics and empirical Bayes methods. It includes a separate chapter on modern numerical techniques for Bayesian inference, and also addresses advanced topics, such as model choice and prediction from frequentist and Bayesian perspectives. This revised edition of the book "Applied Statistical Inference" has been expanded to include new material on Markov models for time series analysis. It also features a comprehensive appendix covering the prerequisites in probability theory, matrix algebra, mathematical calculus, and numerical analysis, and each chapter is complemented by exercises. The text is primarily intended for graduate statistics and biostatistics students with an interest in applications.

ISBN: 9783662607923

Standard No.: 10.1007/978-3-662-60792-3doiSubjects--Topical Terms:

551404
Bayesian statistical decision theory.

LC Class. No.: QA279.5 / .H453 2020

Dewey Class. No.: 519.542

Likelihood and Bayesian inference = with applications in biology and medicine /
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