國立高雄大學圖資館 |

Language: English

Back

System dynamics modeling with R

Duggan, Jim.

System dynamics modeling with R

Record Type:	Electronic resources : Monograph/item
Title/Author:	System dynamics modeling with Rby Jim Duggan.
Author:	Duggan, Jim.
Published:	Cham :Springer International Publishing :2016.
Description:	xviii, 176 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
Subject:	System analysisMathematical models.
Online resource:	http://dx.doi.org/10.1007/978-3-319-34043-2
ISBN:	9783319340432$q(electronic bk.)

System dynamics modeling with R
Duggan, Jim.

System dynamics modeling with R[electronic resource] /by Jim Duggan. - Cham :Springer International Publishing :2016. - xviii, 176 p. :ill. (some col.), digital ;24 cm. - Lecture notes in social networks,2190-5428. - Lecture notes in social networks..

An Introduction to System Dynamics -- An Introduction to R -- Modeling Limits to Growth -- Higher Order Models -- Diffusion Models -- Model Testing -- Model Analysis and Calibration -- Appendix A: Installing R and R Studio.

This new interdisciplinary work presents system dynamics as a powerful approach to enable analysts build simulation models of social systems, with a view toward enhancing decision making. Grounded in the feedback perspective of complex systems, the book provides a practical introduction to system dynamics, and covers key concepts such as stocks, flows, and feedback. Societal challenges such as predicting the impact of an emerging infectious disease, estimating population growth, and assessing the capacity of health services to cope with demographic change can all benefit from the application of computer simulation. This text explains important building blocks of the system dynamics approach, including material delays, stock management heuristics, and how to model effects between different systemic elements. Models from epidemiology, health systems, and economics are presented to illuminate important ideas, and the R programming language is used to provide an open-source and interoperable way to build system dynamics models. System Dynamics Modeling with R also describes hands-on techniques that can enhance client confidence in system dynamic models, including model testing, model analysis, and calibration. Developed from the author's course in system dynamics, this book is written for undergraduate and postgraduate students of management, operations research, computer science, and applied mathematics. Its focus is on the fundamental building blocks of system dynamics models, and its choice of R as a modeling language make it an ideal reference text for those wishing to integrate system dynamics modeling with related data analytic methods and techniques.

ISBN: 9783319340432$q(electronic bk.)

Standard No.: 10.1007/978-3-319-34043-2doiSubjects--Topical Terms:

231631
System analysis
--Mathematical models.

LC Class. No.: QA402

Dewey Class. No.: 004.21

System dynamics modeling with R
LDR:02933nmm a2200349 a 4500 001 490333
003 DE-He213
005 20161117143945.0
006 m d
007 cr nn 008maaau
008 170118s2016 gw s 0 eng d
020 $a 9783319340432$q(electronic bk.)
020 $a 9783319340418$q(paper)
024 7 $a 10.1007/978-3-319-34043-2 $2 doi
035 $a 978-3-319-34043-2
040 $a GP $c GP
041 0 $a eng
050 4 $a QA402
072 7 $a J $2 bicssc
072 7 $a UB $2 bicssc
072 7 $a COM018000 $2 bisacsh
072 7 $a SOC000000 $2 bisacsh
082 0 4 $a 004.21 $2 23
090 $a QA402 $b .D866 2016
100 1 $a Duggan, Jim. $3 749714
245 1 0 $a System dynamics modeling with R $h [electronic resource] / $c by Jim Duggan.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2016.
300 $a xviii, 176 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Lecture notes in social networks, $x 2190-5428
505 0 $a An Introduction to System Dynamics -- An Introduction to R -- Modeling Limits to Growth -- Higher Order Models -- Diffusion Models -- Model Testing -- Model Analysis and Calibration -- Appendix A: Installing R and R Studio.
520 $a This new interdisciplinary work presents system dynamics as a powerful approach to enable analysts build simulation models of social systems, with a view toward enhancing decision making. Grounded in the feedback perspective of complex systems, the book provides a practical introduction to system dynamics, and covers key concepts such as stocks, flows, and feedback. Societal challenges such as predicting the impact of an emerging infectious disease, estimating population growth, and assessing the capacity of health services to cope with demographic change can all benefit from the application of computer simulation. This text explains important building blocks of the system dynamics approach, including material delays, stock management heuristics, and how to model effects between different systemic elements. Models from epidemiology, health systems, and economics are presented to illuminate important ideas, and the R programming language is used to provide an open-source and interoperable way to build system dynamics models. System Dynamics Modeling with R also describes hands-on techniques that can enhance client confidence in system dynamic models, including model testing, model analysis, and calibration. Developed from the author's course in system dynamics, this book is written for undergraduate and postgraduate students of management, operations research, computer science, and applied mathematics. Its focus is on the fundamental building blocks of system dynamics models, and its choice of R as a modeling language make it an ideal reference text for those wishing to integrate system dynamics modeling with related data analytic methods and techniques.
650 0 $a System analysis $x Mathematical models. $3 231631
650 0 $a R (Computer program language) $3 210846
650 1 4 $a Computer Science. $3 212513
650 2 4 $a Computer Appl. in Social and Behavioral Sciences. $3 274376
650 2 4 $a Methodology of the Social Sciences. $3 275266
650 2 4 $a Operation Research/Decision Theory. $3 585050
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a Lecture notes in social networks. $3 679300
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-34043-2
950 $a Computer Science (Springer-11645)