9780387987675 - probabilistic networks and expert systems: exact computational methods for bayesian networks (information science and statistics) von cowell, robert g.; dawid, philip; lauritzen, steffen l.; spiegelhalter, david j. (5 Ergebnisse)
- Hardcover
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Zustand: Good. 1st ed. 1999. Corr. 2nd printing. Former library copy. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.
- Hardcover
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EUR 30,71
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Zustand: Very Good. 1st ed. 1999. Corr. 2nd printing. Former library copy. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.
Probabilistic Networks and Expert Systems: Exact Computational Methods for Bayesian Networks (Information Science and Statistics)
Robert G. Cowell; A. Philip Dawid; Steffen L. Lauritzen; David J. Spiegelhalter
- Hardcover
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Hard Cover. Zustand: Good. No Jacket. Ex-library with the usual features. The interior is clean and tight. Binding is good. Cover shows light wear. 321 pages. Ex-Library.
Probabilistic Networks and Expert Systems: Exact Computational Methods for Bayesian Networks (Information Science and Statistics)
Cowell, Robert G.; Dawid, Philip; Lauritzen, Steffen L.; Spiegelhalter, David J.
- Hardcover
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes KönigreichRia Christie Collections
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EUR 176,03
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Zustand: New. In English.
- Hardcover
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EUR 185,68
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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - WINNER OF THE 2001 DEGROOT PRIZE!Probabilistic expert systems are graphical networks that support the modelling of uncertainty and decisions in large complex domains, while retaining ease of calculation. Building on original research by the authors over a n…umber of years, this book gives a thorough and rigorous mathematical treatment of the underlying ideas, structures, and algorithms, emphasizing those cases in which exact answers are obtainable. It covers both the updating of probabilistic uncertainty in the light of new evidence, and statistical inference, about unknown probabilities or unknown model structure, in the light of new data. The careful attention to detail will make this work an important reference source for all those involved in the theory and applications of probabilistic expert systems.This book was awarded the first DeGroot Prize by the International Society for Bayesian Analysis for a book making an important, timely, thorough, and notably original contribution to the statistics literature.
