Title: Confidence, Likelihood ,and Probability: Statistical Inference With Confidence Distributions
Publisher: Cambridge Univ Pr
Publication Date: 2016
Language: English
ISBN 10: 0521861608
ISBN 13: 9780521861601
Binding: Hardcover
Condition: Brand New
Weight: 1.09 kilograms

About this title

Synopsis

This lively book lays out a methodology of confidence distributions and puts them through their paces. Among other merits they lead to optimal combinations of conﬁdence from different sources of information, and they can make complex models amenable to objective and indeed prior-free analysis for less subjectively inclined statisticians. The generous mixture of theory, illustrations, applications and exercises is suitable for statisticians at all levels of experience, as well as for data-oriented scientists. Some confidence distributions are less dispersed than their competitors. This concept leads to a theory of risk functions and comparisons for distributions of confidence. Neyman-Pearson type theorems leading to optimal confidence are developed and richly illustrated. Exact and optimal confidence distribution is the gold standard for inferred epistemic distributions. Confidence distributions and likelihood functions are intertwined, allowing prior distributions to be made part of the likelihood. Meta-analysis in likelihood terms is developed and taken beyond traditional methods, suiting it in particular to combining information across diverse data sources.

About the Authors

Tore Schweder is a Professor of Statistics in the Department of Economics and at the Centre for Ecology and Evolutionary Synthesis at the University of Oslo.

Nils Lid Hjort is Professor of Mathematical Statistics in the Department of Mathematics at the University of Oslo.

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