Decision Systems and Nonstochastic Randomness

Ivanenko, V. I.

ISBN 10: 144195547X / ISBN 13: 9781441955470

Verlag: Springer, 2010

Beschreibung

Springer Science and Business Media; New York, 2010. Hardcover. A Near Fine, binding firm, interior and extremities tidy, trace handling/scuff marks to boards, mild edge/corner wear, without Dust wrapper. A nice, clean and unmarked copy. 8vo[octavo or approx. 6 x 9 inches], 272pp., reference, indexed. We pack securely and ship daily with delivery confirmation on every book. The picture on the listing page is of the actual book for sale. Additional Scan(s) are available for any item, please inquire.Please note: Oversized books/sets MAY require additional postage then what is quoted for 2.2lb book.

Bestandsnummer des Verkäufers SKU1037154

Bibliografische Details

• Titel: Decision Systems and Nonstochastic Randomness
• Verlag: Springer
• Erscheinungsjahr: 2010
• Sprache: Englisch
• ISBN-10: 144195547X
• ISBN-13: 9781441955470
• Einband: hardcover
• Zustand: As New
• Verkäuferkataloge:
  • Math Text Books

Über diesen Titel

Inhaltsangabe

"Decision Systems and Non-stochastic Randomness" is the first systematic presentation and mathematical formalization (including existence theorems) of the statistical regularities of non-stochastic randomness. The results presented in this book extend the capabilities of probability theory by providing mathematical techniques that allow for the description of uncertain events that do not fit standard stochastic models. The book demonstrates how non-stochastic regularities can be incorporated into decision theory and information theory, offering an alternative to the subjective probability approach to uncertainty and the unified approach to the measurement of information. This book is intended for statisticians, mathematicians, engineers, economists or other researchers interested in non-stochastic modeling and decision theory.

Von der hinteren Coverseite

Decision Systems and Nonstochastic Randomness presents the first mathematical formalization of the statistical regularities of non-stochastic randomness and demonstrates how these regularities extend the standard probability-based model of decision making under uncertainty, allowing for the description of uncertain mass events that do not fit standard stochastic models.Each self-contained chapter of this neatly-structured monograph includes a detailed introduction and summary of its contents. The included results are presented not only with rigorous proofs but also through numerous intuitive examples. An appendix is provided which includes classic results from the theory of functions and measured sets as well as decision theory, offering an overview of the necessary prerequisites.The formalism of statistical regularities developed in this book will have a significant influence on decision theory and information theory as well as numerous other disciplines. Because of these far-reaching implications, this book may be a useful resource for statisticians, mathematicians, engineers, economists and other utilizing nonstochastic modeling and decision theory.