Posted by **AlenMiler** at Aug. 19, 2014

November 25, 2013 | ISBN: 3642378862 | Pages: 376 | PDF | 8 MB

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.

Posted by **Specialselection** at Feb. 15, 2014

English | 2010-09-20 | ISBN: 0521192498 | 276 pages | PDF | 3.6 mb

Posted by **fdts** at Dec. 1, 2016

by G. A. Young, R. L. Smith

English | 2005 | ISBN: 0521839718 | 236 pages | PDF | 2.91 MB

Posted by **interes** at Nov. 25, 2016

English | 2016 | ISBN: 3319440926 | 220 pages | PDF | 7 MB

Posted by **interes** at Nov. 24, 2016

English | 2016 | ISBN: 3319416421 | 243 pages | PDF | 4,3 MB

Posted by **Willson** at Nov. 7, 2016

English | 2006 | ISBN: 0470008741 | 544 pages | DJVU | 6.4 MB

Posted by **Willson** at Nov. 2, 2016

English | 2009 | ISBN: 052189560X | 484 pages | PDF | 7.3 MB

Posted by **Willson** at Oct. 29, 2016

English | 1988 | ISBN: 1558604790 | 552 pages | PDF | 56 MB

Posted by **tanas.olesya** at Oct. 20, 2016

English | 7 Aug. 2009 | ISBN: 0123748542 | 325 Pages | PDF | 4 MB

This text is written to provide a mathematically sound but accessible and engaging introduction to Bayesian inference specifically for environmental scientists, ecologists and wildlife biologists. It emphasizes the power and usefulness of Bayesian methods in an ecological context.

Posted by **tanas.olesya** at Oct. 17, 2016

English | 25 Oct. 2001 | ISBN: 0521001013, 0521800641 | 312 Pages | PDF | 3 MB

Coping with uncertainty is a necessary part of ordinary life and is crucial to an understanding of how the mind works. For example, it is a vital element in developing artificial intelligence that will not be undermined by its own rigidities.