Probabilistic Techniques in Exposure Assessment: A Handbook for Dealing with Variability and Uncertainty in Models and Inputs

Cullen, Alison C.; Frey, H. Christopher

ISBN 10: 0306459566 / ISBN 13: 9780306459566

Published by Springer, 1999

About this Item

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Seller Inventory # SHUB72454

Bibliographic Details

• Title: Probabilistic Techniques in Exposure Assessment: A Handbook for Dealing with Variability and Uncertainty in Models and Inputs
• Publisher: Springer
• Publication Date: 1999
• Language: English
• ISBN 10: 0306459566
• ISBN 13: 9780306459566
• Binding: Hardcover
• Condition: New

About this title

Synopsis

At this time when regulatory agencies are accepting and actively encouraging probabilistic approaches and the attribution of overall uncertainty among inputs to support Value of Information analyses, a comprehensive sourcebook on methods for addressing variability and uncertainty in exposure analysis is sorely needed. This need is adroitly met in Probabilistic Techniques in Exposure Assessment. A host of expert contributors provide a straightforward introduction to the practical tools for addressing variability and uncertainty in support of environmental and human health decision making. 151 graphs, plots, charts, and figures supplement a broad range of detailed and practical examples.

Review

`...the various topics are presented extremely well from the pedagogic point of view. For readers of this journal, the most appealing feature of the book is its extensive coverage of systems modeling and simulation . Other good features of the book include: careful examination of assumptions under which probabilistic modeling is a useful and justified; excellent discussion of the many aspects of uncertainty and variability; unusually good and extensive (80-page long) coverage of probability distributions; interesting and well-described examples and the case studies in the area of risk analysis; and a useful glossary of technical terms. In summary, this is an excellent book for anyone interested in probabilistic modeling. In my opinion, it is the right book in this domain for readers of this journal and I highly recommend it.'
International Journal of General Systems, 31(1):97-110, (2002)