---

＜電子ブック＞
Applied Statistical Inference : Likelihood and Bayes / by Leonhard Held, Daniel Sabanés Bové

版	1st ed. 2014.
出版者	(Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer)
出版年	2014
本文言語	英語
大きさ	XIII, 376 p. 71 illus : online resource
著者標目	*Held, Leonhard author Sabanés Bové, Daniel author SpringerLink (Online service)
件　名	LCSH:Statistics  LCSH:Biometry LCSH:Mathematical statistics -- Data processing  全ての件名で検索 FREE:Statistical Theory and Methods FREE:Biostatistics FREE:Statistics and Computing
一般注記	This book covers modern statistical inference based on likelihood with applications in medicine, epidemiology and biology. Two introductory chapters discuss the importance of statistical models in applied quantitative research and the central role of the likelihood function. The rest of the book is divided into three parts. The first describes likelihood-based inference from a frequentist viewpoint.  Properties of the maximum likelihood estimate, the score function, the likelihood ratio and the Wald statistic are discussed in detail. In the second part, 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. Modern numerical techniques for Bayesian inference are described in a separate chapter. Finally two more advanced topics, model choice and prediction, are discussed both from a frequentist and a Bayesian perspective.   A comprehensive appendix covers the necessary prerequisites in probability theory, matrix algebra, mathematical calculus, and numerical analysis HTTP:URL=https://doi.org/10.1007/978-3-642-37887-4

 類似資料