TY - BOOK AU - Rocquigny,Etienne de ED - Wiley InterScience (Online service) TI - Modelling under risk and uncertainty: an introduction to statistical, phenomenological, and computational methods T2 - Wiley series in probability and statistics SN - 9781119969495 AV - HD30.25 .R63 2012 U1 - 338.501/5195 23 PY - 2012/// CY - Hoboken, NJ PB - Wiley KW - Industrial management KW - Mathematical models KW - Uncertainty KW - Risk management KW - MATHEMATICS KW - Probability & Statistics KW - General KW - bisacsh KW - fast KW - Electronic books N1 - Includes bibliographical references and index; Front Matter -- Applications and Practices of Modelling, Risk and Uncertainty -- A Generic Modelling Framework -- A Generic Tutorial Example: Natural Risk in an Industrial Installation -- Understanding Natures of Uncertainty, Risk Margins and Time Bases for Probabilistic Decision-Making -- Direct Statistical Estimation Techniques -- Combined Model Estimation through Inverse Techniques -- Computational Methods for Risk and Uncertainty Propagation -- Optimising Under Uncertainty: Economics and Computational Challenges -- Conclusion: Perspectives of Modelling in the Context of Risk and Uncertainty and Further Research -- Annexes -- Epilogue -- Index -- Wiley Series in Probability and Statistics; ps N2 - "This volume addresses a concern of very high relevance and growing interest for large industries or environmentalists: risk and uncertainty in complex systems. It gives new insight on the peculiar mathematical challenges generated by recent industrial safety or environmental control analysis, focusing on implementing decision theory choices related to risk and uncertainty analysis through statistical estimation and computation, in the presence of physical modeling and risk analysis. The result will lead statisticians and associated professionals to formulate and solve new challenges at the frontier between statistical modeling, physics, scientific computing, and risk analysis"--; "This book aims at giving a new insight on the peculiar mathematical challenges generated by recent industrial safety or environmental control analysis"-- UR - http://dx.doi.org/10.1002/9781119969495 ER -