大葉大學圖書館 |

Robust simulation for mega-risks[electronic resource] :the path from single-solution to competitive, multi-solution methods for mega-risk management /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
杜威分類號:	363.34
書名/作者:	Robust simulation for mega-risks : the path from single-solution to competitive, multi-solution methods for mega-risk management // by Craig E. Taylor.
作者:	Taylor, Craig E.
出版者:	Cham : : Springer International Publishing :, 2015.
面頁冊數:	xxi, 164 p. : : ill., digital ;; 24 cm.
Contained By:	Springer eBooks
標題:	Emergency management.
標題:	Risk management - Planning.
標題:	Crisis management.
標題:	Earth Sciences.
標題:	Natural Hazards.
標題:	Simulation and Modeling.
標題:	Complex Systems.
ISBN:	9783319194134
ISBN:	9783319194127
內容註:	Introduction: 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.
摘要、提要註:	This 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.
電子資源:	http://dx.doi.org/10.1007/978-3-319-19413-4

Robust simulation for mega-risks[electronic resource] :the path from single-solution to competitive, multi-solution methods for mega-risk management /
Taylor, Craig E.

Robust simulation for mega-risksthe path from single-solution to competitive, multi-solution methods for mega-risk management /[electronic resource] :by Craig E. Taylor. - Cham :Springer International Publishing :2015. - xxi, 164 p. :ill., digital ;24 cm.

Introduction: 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.

This 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.

ISBN: 9783319194134

Standard No.: 10.1007/978-3-319-19413-4doiSubjects--Topical Terms:

181965
Emergency management.

LC Class. No.: HV551.2

Dewey Class. No.: 363.34

Robust simulation for mega-risks[electronic resource] :the path from single-solution to competitive, multi-solution methods for mega-risk management /
LDR:02738nam a2200313 a 4500 001 444090
003 DE-He213
005 20160502162838.0
006 m d
007 cr nn 008maaau
008 160715s2015 gw s 0 eng d
020 $a 9783319194134 $q (electronic bk.)
020 $a 9783319194127 $q (paper)
024 7 $a 10.1007/978-3-319-19413-4 $2 doi
035 $a 978-3-319-19413-4
040 $a GP $c GP
041 0 $a eng
050 4 $a HV551.2
072 7 $a RNR $2 bicssc
072 7 $a NAT023000 $2 bisacsh
082 0 4 $a 363.34 $2 23
090 $a HV551.2 $b .T238 2015
100 1 $a Taylor, Craig E. $3 635269
245 1 0 $a Robust simulation for mega-risks $h [electronic resource] : $b the path from single-solution to competitive, multi-solution methods for mega-risk management / $c by Craig E. Taylor.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2015.
300 $a xxi, 164 p. : $b ill., digital ; $c 24 cm.
505 0 $a Introduction: 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 $a This 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 $a Emergency management. $3 181965
650 0 $a Risk management $x Planning. $3 635270
650 0 $a Crisis management. $3 184593
650 1 4 $a Earth Sciences. $3 463803
650 2 4 $a Natural Hazards. $3 463804
650 2 4 $a Simulation and Modeling. $3 463796
650 2 4 $a Complex Systems. $3 465366
710 2 $a SpringerLink (Online service) $3 463450
773 0 $t Springer eBooks
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-19413-4
950 $a Earth and Environmental Science (Springer-11646)