Martin / Liu Inferential Models

Reasoning with Uncertainty
Erscheinungsjahr 2015
ISBN: 978-1-4398-8651-9
Verlag: CRC Press
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 276 Seiten

Reihe: Chapman & Hall/CRC Monographs on Statistics & Applied Probability

This book delves into the authors’ work toward deeper understanding of statistical inference in terms of reasoning with uncertainty and meaningfulness of probabilistic inferential output. Focusing on a valid, prior-free probabilistic inferential framework called inferential models, the authors explain how to first identify the underlying source of uncertainty as an integral part of statistical modeling and then make probabilistic inference by calculating the predictable quantity in a statistically accurate way.

Zielgruppe

Scientists, researchers, statisticians, and graduate and undergraduate students interested in valid probabilistic inference.

Autoren/Hrsg.

Martin, Ryan

Liu, Chuanhai

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik

Inhaltsverzeichnis

Introduction. Inferential Models. Conditional Inferential Models. Marginal Inferential Models. Inferential Models and Likelihood-Based Inference. Bibliography.