Sprache: Englisch
Verlag: Cambridge University Press, 2003
ISBN 10: 0521592712 ISBN 13: 9780521592710
Anbieter: Books From California, Simi Valley, CA, USA
Hardcover. Zustand: Fine.
Sprache: Englisch
Verlag: Cambridge University Press, 2003
ISBN 10: 0521592712 ISBN 13: 9780521592710
Anbieter: Books From California, Simi Valley, CA, USA
Hardcover. Zustand: Very Good. The binding shows minor marks and dents, but the copy is in otherwise clean condition.
Anbieter: Anybook.com, Lincoln, Vereinigtes Königreich
EUR 95,30
Anzahl: 1 verfügbar
In den WarenkorbZustand: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,450grams, ISBN:0387968717.
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
EUR 149,17
Anzahl: 2 verfügbar
In den WarenkorbPaperback. Zustand: Brand New. 221 pages. 11.90x7.10x1.00 inches. In Stock.
Sprache: Englisch
Verlag: Cambridge University Press, 2003
ISBN 10: 0521592712 ISBN 13: 9780521592710
Anbieter: Buchkanzlei, Bremen, Deutschland
Hardcover. Zustand: Gut. 758 pp. Cover slightly rubbed at the edges, with some pressure marks and scratches and slightly discolored at spine. Well preserved inside 354 Sprache: Englisch Gewicht in Gramm: 180.
Sprache: Englisch
Verlag: Springer New York, Springer New York, 1988
ISBN 10: 0387968717 ISBN 13: 9780387968711
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This work is essentially an extensive revision of my Ph.D. dissertation, [1J. It 1S primarily a research document on the application of probability theory to the parameter estimation problem. The people who will be interested in this material are physicists, economists, and engineers who have to deal with data on a daily basis; consequently, we have included a great deal of introductory and tutorial material. Any person with the equivalent of the mathematics background required for the graduate level study of physics should be able to follow the material contained in this book, though not without eIfort. From the time the dissertation was written until now (approximately one year) our understanding of the parameter estimation problem has changed extensively. We have tried to incorporate what we have learned into this book. I am indebted to a number of people who have aided me in preparing this docu ment: Dr. C. Ray Smith, Steve Finney, Juana Sunchez, Matthew Self, and Dr. Pat Gibbons who acted as readers and editors. In addition, I must extend my deepest thanks to Dr. Joseph Ackerman for his support during the time this manuscript was being prepared.
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
EUR 197,48
Anzahl: 2 verfügbar
In den WarenkorbHardcover. Zustand: Brand New. 1st edition. 753 pages. 10.25x7.25x1.50 inches. In Stock.
Sprache: Englisch
Verlag: Cambridge University Press, 2003
ISBN 10: 0521592712 ISBN 13: 9780521592710
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The standard rules of probability can be interpreted as uniquely valid principles in logic. In this book, E. T. Jaynes dispels the imaginary distinction between 'probability theory' and 'statistical inference', leaving a logical unity and simplicity, which provides greater technical power and flexibility in applications. This book goes beyond the conventional mathematics of probability theory, viewing the subject in a wider context. New results are discussed, along with applications of probability theory to a wide variety of problems in physics, mathematics, economics, chemistry and biology. It contains many exercises and problems, and is suitable for use as a textbook on graduate level courses involving data analysis. The material is aimed at readers who are already familiar with applied mathematics at an advanced undergraduate level or higher. The book will be of interest to scientists working in any area where inference from incomplete information is necessary.