Inferential Models - Couverture souple

Martin, Ryan; Liu, Chuanhai

Couverture souple

ISBN 10 : 0367737809 ISBN 13 : 9780367737801

Editeur : Routledge, 2020

Synopsis

A New Approach to Sound Statistical Reasoning

Inferential Models: Reasoning with Uncertainty introduces the authors' recently developed approach to inference: the inferential model (IM) framework. This logical framework for exact probabilistic inference does not require the user to input prior information. The authors show how an IM produces meaningful prior-free probabilistic inference at a high level.

The book covers the foundational motivations for this new IM approach, the basic theory behind its calibration properties, a number of important applications, and new directions for research. It discusses alternative, meaningful probabilistic interpretations of some common inferential summaries, such as p-values. It also constructs posterior probabilistic inferential summaries without a prior and Bayes' formula and offers insight on the interesting and challenging problems of conditional and marginal inference.

This book delves into statistical inference at a foundational level, addressing what the goals of statistical inference should be. It explores a new way of thinking compared to existing schools of thought on statistical inference and encourages you to think carefully about the correct approach to scientific inference.

A propos du livre

À propos de l?auteur

Ryan Martin is an associate professor in the Department of Mathematics, Statistics, and Computer Science at the University of Illinois at Chicago.

Chuanhai Liu is a professor in the Department of Statistics at Purdue University.

Détails de l'édition

• Éditeur: Routledge
• Date d'édition: 2020
• Langue: anglais
• ISBN 10: 0367737809
• ISBN 13: 9780367737801
• Reliure: Broché
• Nombre de pages: 276
• Coordonnées du fabricant: non disponible
• Personne responsable: non disponible