A Comparison Of The Bayesian And Frequentist Approaches To Estimation
Download A Comparison Of The Bayesian And Frequentist Approaches To Estimation PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get A Comparison Of The Bayesian And Frequentist Approaches To Estimation book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
A Comparison of the Bayesian and Frequentist Approaches to Estimation
Author: Francisco J. Samaniego
language: en
Publisher: Springer Science & Business Media
Release Date: 2010-06-14
The main theme of this monograph is “comparative statistical inference. ” While the topics covered have been carefully selected (they are, for example, restricted to pr- lems of statistical estimation), my aim is to provide ideas and examples which will assist a statistician, or a statistical practitioner, in comparing the performance one can expect from using either Bayesian or classical (aka, frequentist) solutions in - timation problems. Before investing the hours it will take to read this monograph, one might well want to know what sets it apart from other treatises on comparative inference. The two books that are closest to the present work are the well-known tomes by Barnett (1999) and Cox (2006). These books do indeed consider the c- ceptual and methodological differences between Bayesian and frequentist methods. What is largely absent from them, however, are answers to the question: “which - proach should one use in a given problem?” It is this latter issue that this monograph is intended to investigate. There are many books on Bayesian inference, including, for example, the widely used texts by Carlin and Louis (2008) and Gelman, Carlin, Stern and Rubin (2004). These books differ from the present work in that they begin with the premise that a Bayesian treatment is called for and then provide guidance on how a Bayesian an- ysis should be executed. Similarly, there are many books written from a classical perspective.
Ecological Inference
Author: Gary King
language: en
Publisher: Cambridge University Press
Release Date: 2004-09-13
Drawing upon the recent explosion of research in the field, a diverse group of scholars surveys the latest strategies for solving ecological inference problems, the process of trying to infer individual behavior from aggregate data. The uncertainties and information lost in aggregation make ecological inference one of the most difficult areas of statistical inference, but these inferences are required in many academic fields, as well as by legislatures and the Courts in redistricting, marketing research by business, and policy analysis by governments. This wide-ranging collection of essays offers many fresh and important contributions to the study of ecological inference.
In All Likelihood
Author: Yudi Pawitan
language: en
Publisher: Oxford University Press, USA
Release Date: 2013-01-17
This book introduces likelihood as a unifying concept in statistical modelling and inference. The complete range of concepts and applications are covered, from very simple to very complex studies. It relies on realistic examples, and presents the main results using heuristic rather than formal mathematical arguments.