Advances in Info-Metrics
Information and Information Processing across Disciplines
Aman Ullah editor Min Chen editor J Michael Dunn editor Amos Golan editor
Format:Hardback
Publisher:Oxford University Press Inc
Published:20th Jan '21
Should be back in stock very soon
Info-metrics is a framework for modeling, reasoning, and drawing inferences under conditions of noisy and insufficient information. It is an interdisciplinary framework situated at the intersection of information theory, statistical inference, and decision-making under uncertainty. In Advances in Info-Metrics, Min Chen, J. Michael Dunn, Amos Golan, and Aman Ullah bring together a group of thirty experts to expand the study of info-metrics across the sciences and demonstrate how to solve problems using this interdisciplinary framework. Building on the theoretical underpinnings of info-metrics, the volume sheds new light on statistical inference, information, and general problem solving. The book explores the basis of information-theoretic inference and its mathematical and philosophical foundations. It emphasizes the interrelationship between information and inference and includes explanations of model building, theory creation, estimation, prediction, and decision making. Each of the nineteen chapters provides the necessary tools for using the info-metrics framework to solve a problem. The collection covers recent developments in the field, as well as many new cross-disciplinary case studies and examples. Designed to be accessible for researchers, graduate students, and practitioners across disciplines, this book provides a clear, hands-on experience for readers interested in solving problems when presented with incomplete and imperfect information.
The book should be of interest to researchers and practitioners who need to present convincing conclusions, and would make a good addition to libraries supporting advanced studies in computer and information sciences. * R. Bharath, emeritus, Northern Michigan University, CHOICE *
Information permeates every corner of our lives and shapes our universe. Advances in Info-Metrics expands the study of info-metrics and provides a framework for modeling, reasoning, and drawing inferences across disciplines. It explores philosophical and mathematical foundations of information. It also demonstrates how to solve problems through many cross-disciplinary examples arising in biology, medicine, economy, and data science. * Wojciech Szpankowski, Saul Rosen Professor of Computer Science, Purdue University *
This volume has emerged from the Info-metrics Institute, set up by one of the authors, Professor Golan, over a decade ago. The Institute has since done much to stimulate research in a broad area of theoretical and empirical statistics. The present volume, consisting of many and varied research papers, should certainly be valuable in stimulating further research. * Peter M. Robinson, Tooke Emeritus Professor of Economic Science and Statistics, London School of Economics *
Impressive contributions in this volume address many aspects of information theory concepts, measures, and applications. It is a multidisciplinary tour de force, covering foundations, inference, and applications to finance, computing, behavioral models, and much more. * Esfandiar Maasoumi, Arts & Sciences Distinguished Professor, Emory University *
ISBN: 9780190636685
Dimensions: 168mm x 249mm x 33mm
Weight: 1089g
560 pages