Applied Statistical Inference PDF
By:Leonhard Held,Daniel Sabanés Bové
Published on 2013-11-12 by Springer Science & Business Media
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.
This Book was ranked at 20 by Google Books for keyword Biostatistics.
Book ID of Applied Statistical Inference's Books is Xv3FBAAAQBAJ, Book which was written byLeonhard Held,Daniel Sabanés Bovéhave ETAG "EsM+G07pamg"
Book which was published by Springer Science & Business Media since 2013-11-12 have ISBNs, ISBN 13 Code is 9783642378874 and ISBN 10 Code is 3642378870
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Book which have "376 Pages" is Printed at BOOK under CategoryMathematics
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