東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Uncertainty quantification using R

Cursi, Eduardo Souza de.

Linked to FindBook

Google Book

Amazon

博客來

Uncertainty quantification using R

Record Type:	Electronic resources : Monograph/item
Title/Author:	Uncertainty quantification using R/ by Eduardo Souza de Cursi.
Author:	Cursi, Eduardo Souza de.
Published:	Cham :Springer International Publishing : : 2023.,
Description:	x, 766 p. :ill., digital ;24 cm.
[NT 15003449]:	1. Introduction -- 2. Some tips to use R and RStudio -- 3. Probabilities and Random Variables -- 4. Representation of random variables -- 5. Stochastic processes -- 6. Uncertain Algebraic Equations -- 7. Random Differential Equations -- 8. UQ in Game Theory -- 9. Optimization under uncertainty -- 10. Reliability.
Contained By:	Springer Nature eBook
Subject:	Uncertainty - Mathematical models. -
Online resource:	https://doi.org/10.1007/978-3-031-17785-9
ISBN:	9783031177859

Uncertainty quantification using R
Cursi, Eduardo Souza de.

Uncertainty quantification using R[electronic resource] /by Eduardo Souza de Cursi. - Cham :Springer International Publishing :2023. - x, 766 p. :ill., digital ;24 cm. - International series in operations research & management science,v. 3352214-7934 ;. - International series in operations research & management science ;v. 335..

1. Introduction -- 2. Some tips to use R and RStudio -- 3. Probabilities and Random Variables -- 4. Representation of random variables -- 5. Stochastic processes -- 6. Uncertain Algebraic Equations -- 7. Random Differential Equations -- 8. UQ in Game Theory -- 9. Optimization under uncertainty -- 10. Reliability.

This book is a rigorous but practical presentation of the techniques of uncertainty quantification, with applications in R and Python. This volume includes mathematical arguments at the level necessary to make the presentation rigorous and the assumptions clearly established, while maintaining a focus on practical applications of uncertainty quantification methods. Practical aspects of applied probability are also discussed, making the content accessible to students. The introduction of R and Python allows the reader to solve more complex problems involving a more significant number of variables. Users will be able to use examples laid out in the text to solve medium-sized problems. The list of topics covered in this volume includes linear and nonlinear programming, Lagrange multipliers (for sensitivity), multi-objective optimization, game theory, as well as linear algebraic equations, and probability and statistics. Blending theoretical rigor and practical applications, this volume will be of interest to professionals, researchers, graduate and undergraduate students interested in the use of uncertainty quantification techniques within the framework of operations research and mathematical programming, for applications in management and planning.

ISBN: 9783031177859

Standard No.: 10.1007/978-3-031-17785-9doiSubjects--Topical Terms:

648813
Uncertainty
--Mathematical models.

LC Class. No.: QA273 / .C87 2023

Dewey Class. No.: 519.2

Uncertainty quantification using R
LDR:02701nmm a2200361 a 4500 001 2315498
003 DE-He213
005 20230222094919.0
006 m d
007 cr nn 008maaau
008 230902s2023 sz s 0 eng d
020 $a 9783031177859 $q (electronic bk.)
020 $a 9783031177842 $q (paper)
024 7 $a 10.1007/978-3-031-17785-9 $2 doi
035 $a 978-3-031-17785-9
040 $a GP $c GP
041 0 $a eng
050 4 $a QA273 $b .C87 2023
072 7 $a KJT $2 bicssc
072 7 $a KJMD $2 bicssc
072 7 $a BUS049000 $2 bisacsh
072 7 $a KJT $2 thema
072 7 $a KJMD $2 thema
082 0 4 $a 519.2 $2 23
090 $a QA273 $b .C977 2023
100 1 $a Cursi, Eduardo Souza de. $3 2198496
245 1 0 $a Uncertainty quantification using R $h [electronic resource] / $c by Eduardo Souza de Cursi.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2023.
300 $a x, 766 p. : $b ill., digital ; $c 24 cm.
490 1 $a International series in operations research & management science, $x 2214-7934 ; $v v. 335
505 0 $a 1. Introduction -- 2. Some tips to use R and RStudio -- 3. Probabilities and Random Variables -- 4. Representation of random variables -- 5. Stochastic processes -- 6. Uncertain Algebraic Equations -- 7. Random Differential Equations -- 8. UQ in Game Theory -- 9. Optimization under uncertainty -- 10. Reliability.
520 $a This book is a rigorous but practical presentation of the techniques of uncertainty quantification, with applications in R and Python. This volume includes mathematical arguments at the level necessary to make the presentation rigorous and the assumptions clearly established, while maintaining a focus on practical applications of uncertainty quantification methods. Practical aspects of applied probability are also discussed, making the content accessible to students. The introduction of R and Python allows the reader to solve more complex problems involving a more significant number of variables. Users will be able to use examples laid out in the text to solve medium-sized problems. The list of topics covered in this volume includes linear and nonlinear programming, Lagrange multipliers (for sensitivity), multi-objective optimization, game theory, as well as linear algebraic equations, and probability and statistics. Blending theoretical rigor and practical applications, this volume will be of interest to professionals, researchers, graduate and undergraduate students interested in the use of uncertainty quantification techniques within the framework of operations research and mathematical programming, for applications in management and planning.
650 0 $a Uncertainty $x Mathematical models. $3 648813
650 0 $a Predicate calculus. $3 1232949
650 0 $a R (Computer program language) $3 784593
650 1 4 $a Operations Research and Decision Theory. $3 3591727
650 2 4 $a Applied Probability. $3 3599446
650 2 4 $a Discrete Optimization. $3 2054320
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a International series in operations research & management science ; $v v. 335. $3 3627894
856 4 0 $u https://doi.org/10.1007/978-3-031-17785-9
950 $a Business and Management (SpringerNature-41169)