Likelihood and Bayesian Inference: With Applications in Biology and Medicine - Brossura

Libro 64 di 69: Statistics for Biology and Health

Held, Leonhard; Sabanés Bové, Daniel

 
9783662607947: Likelihood and Bayesian Inference: With Applications in Biology and Medicine
Brossura
ISBN 10: 3662607948 ISBN 13: 9783662607947
Casa editrice: Springer, 2021

Sinossi

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.



Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

Informazioni sull?autore

Leonhard Held is a Full Professor of Biostatistics, Director of the Master’s Program in Biostatistics and Chair of the Center for Reproducible Science at the University of Zurich, Switzerland. He has published several books and numerous articles on statistical methodology, applied statistics and biomedical research and teaches undergraduate and graduate-level courses in Biostatistics and Medical Statistics.

Daniel Sabanés Bové completed his PhD in Statistics at the University of Zurich under the supervision of Leonhard Held. He started his career as a biostatistician in oncology drug development at Hoffmann-La Roche in 2013, and has been a data scientist at Google since 2018.


Dalla quarta di copertina

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.


Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.

Editore
Springer
Data di pubblicazione
2021
Lingua
Inglese
ISBN 10 
3662607948
ISBN 13 
9783662607947
Rilegatura
Copertina flessibile
Numero edizione
2
Numero di pagine
416
Contatto del produttore
ProductSafety@springernature.com
ProductSafety@springernature.com

Poststr. 9
Darmstadt
64293
Germania

Altre edizioni note dello stesso titolo

9783662607916: Likelihood and Bayesian Inference: With Applications in Biology and Medicine

Edizione in evidenza

ISBN 10:  3662607913 ISBN 13:  9783662607916
Casa editrice: Springer, 2020
Rilegato