000 03505nam a22005055i 4500
001 978-3-319-19413-4
003 DE-He213
005 20160615101737.0
007 cr nn 008mamaa
008 151111s2015 gw | s |||| 0|eng d
020 _a9783319194134
_9978-3-319-19413-4
024 7 _a10.1007/978-3-319-19413-4
_2doi
049 _aAlfaisal Main Library
050 4 _aGB5000-5030
072 7 _aRNR
_2bicssc
072 7 _aNAT023000
_2bisacsh
082 0 4 _a551
_223
100 1 _aTaylor, Craig E.
_eauthor.
245 1 0 _aRobust Simulation for Mega-Risks
_h[electronic resource] :
_bThe Path from Single-Solution to Competitive, Multi-Solution Methods for Mega-Risk Management /
_cby Craig E. Taylor.
250 _a1st ed. 2015.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2015.
300 _aXXI, 164 p. 21 illus., 9 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aIntroduction: Initial Queries Going Forward -- The Deductivist Theory of Probability and Statistics -- The Frequency Theory of Probability -- Probability and Randomness as Beliefs: Bayesian Theory -- More Challenges to Tradition: Extreme Value Diagnostics, Power Laws, and the Wobble -- Mathematization of Statistics: Flexibility and Convergence -- Robust Simulation and Non-linear Reasoning: Quantitative and Qualitative Examples -- Managing Expectations: Qualitative Considerations And Quantitative Decision Procedures -- Conclusions and Queries.
520 _aThis book introduces a new way of analyzing, measuring and thinking about mega-risks, a “paradigm shift” that moves from single-solutions to multiple competitive solutions and strategies.  “Robust simulation” is a statistical approach that demonstrates future risk through simulation of a suite of possible answers.   To arrive at this point, the book systematically walks through the historical statistical methods for evaluating risks. The first chapters deal with three theories of probability and statistics that have been dominant in the 20th century, along with key mathematical issues and dilemmas.   The book then introduces “robust simulation” which solves the problem of measuring the stability of simulated losses, incorporates outliers, and simulates future risk through a suite of possible answers and stochastic modeling of unknown variables.  This book discusses various analytical methods for utilizing divergent solutions in making pragmatic financial and risk-mitigation decisions.   The book emphasizes the importance of flexibility and attempts to demonstrate that alternative credible approaches are helpful and required in understanding a great many phenomena.    .
650 0 _aEarth sciences.
650 0 _aNatural disasters.
650 0 _aComputer simulation.
650 0 _aSystem theory.
650 1 4 _aEarth Sciences.
650 2 4 _aNatural Hazards.
650 2 4 _aSimulation and Modeling.
650 2 4 _aComplex Systems.
655 7 _aElectronic books.
_2local
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319194127
856 4 0 _uhttp://ezproxy.alfaisal.edu/login?url=http://dx.doi.org/10.1007/978-3-319-19413-4
912 _aZDB-2-EES
942 _2lcc
_cEBOOKS
999 _c265390
_d265390