國立虎尾科技大學 |

Robust Simulation for Mega-Risks = 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
正題名/作者:	Robust Simulation for Mega-Risks/ by Craig E. Taylor.
其他題名:	The Path from Single-Solution to Competitive, Multi-Solution Methods for Mega-Risk Management /
作者:	Taylor, Craig E.
面頁冊數:	XXI, 164 p. 21 illus., 9 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Natural disasters. -
電子資源:	https://doi.org/10.1007/978-3-319-19413-4
ISBN:	9783319194134

Robust Simulation for Mega-Risks = 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. - 1st ed. 2015. - XXI, 164 p. 21 illus., 9 illus. in color.online resource.

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:

555029
Natural disasters.

LC Class. No.: GB5000-5030

Dewey Class. No.: 551

Robust Simulation for Mega-Risks = The Path from Single-Solution to Competitive, Multi-Solution Methods for Mega-Risk Management /
LDR:03207nam a22003975i 4500 001 959941
003 DE-He213
005 20200704074518.0
007 cr nn 008mamaa
008 201211s2015 gw | s |||| 0|eng d
020 $a 9783319194134 $9 978-3-319-19413-4
024 7 $a 10.1007/978-3-319-19413-4 $2 doi
035 $a 978-3-319-19413-4
050 4 $a GB5000-5030
072 7 $a RNR $2 bicssc
072 7 $a NAT023000 $2 bisacsh
072 7 $a RNR $2 thema
082 0 4 $a 551 $2 23
100 1 $a Taylor, Craig E. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1069490
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.
250 $a 1st ed. 2015.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2015.
300 $a XXI, 164 p. 21 illus., 9 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
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 Natural disasters. $3 555029
650 0 $a Computer simulation. $3 560190
650 0 $a System theory. $3 566168
650 1 4 $a Natural Hazards. $3 784090
650 2 4 $a Simulation and Modeling. $3 669249
650 2 4 $a Complex Systems. $3 888664
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783319194127
776 0 8 $i Printed edition: $z 9783319194141
776 0 8 $i Printed edition: $z 9783319369075
856 4 0 $u https://doi.org/10.1007/978-3-319-19413-4
912 $a ZDB-2-EES
912 $a ZDB-2-SXEE
950 $a Earth and Environmental Science (SpringerNature-11646)
950 $a Earth and Environmental Science (R0) (SpringerNature-43711)