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Likelihood and Bayesian Inference = ...
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Likelihood and Bayesian Inference = With Applications in Biology and Medicine /
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Likelihood and Bayesian Inference/ by Leonhard Held, Daniel Sabanés Bové.
Reminder of title:
With Applications in Biology and Medicine /
Author:
Held, Leonhard.
other author:
Sabanés Bové, Daniel.
Description:
XIII, 402 p. 84 illus.online resource. :
Contained By:
Springer Nature eBook
Subject:
Statistics . -
Online resource:
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 Inference
With Applications in Biology and Medicine /[electronic resource] :by Leonhard Held, Daniel Sabanés Bové. - 2nd ed. 2020. - XIII, 402 p. 84 illus.online resource. - 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:
1253516
Statistics .
LC Class. No.: QA276-280
Dewey Class. No.: 519.5
Likelihood and Bayesian Inference = With Applications in Biology and Medicine /
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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.
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