Confidence, Likelihood, Probability: Statistical Inference with Confidence Distributions

Tore Schweder · Nils Lid Hjort

२०१६ फेब्रुअरी · Cambridge Series in Statistical and Probabilistic Mathematics पुस्तक 41 · Cambridge University Press

इ-पुस्तक

521

पृष्ठहरू

रेटिङ र रिभ्यूहरूको पुष्टि गरिएको हुँदैन थप जान्नुहोस्

यो इ-पुस्तकका बारेमा

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.

लेखकको बारेमा

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.

यो इ-पुस्तकको मूल्याङ्कन गर्नुहोस्

हामीलाई आफ्नो धारणा बताउनुहोस्।

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