Graph algebra : mathematical modeling with a systems approach

著者

• Brown, Courtney

書誌事項

Graph algebra : mathematical modeling with a systems approach

Courtney Brown

（Sage publications series, . Quantitative applications in the social sciences ; no. 07-151）

Sage Publications, c2008

• : pbk

注記

Includes bibliographical references and index

内容説明・目次

内容説明

"Brown is well known for research on mathematical modeling in the social sciences. His book introduces the graph algebra approach to modeling systems in the social sciences." -CHOICE Graph Algebra: Mathematical Modeling with a Systems Approach introduces a new modeling tool to students and researchers in the social sciences. Derived from engineering literature that uses similar techniques to map electronic circuits and physical systems, graph algebra utilizes a systems approach to modeling that offers social scientists a variety of tools that are both sophisticated and easily applied. Key Features: Designed for readers in the social sciences with minimal mathematical training: In this volume, the author assists readers in developing their own difference and differential equation model specifications Incorporates Social Theory: This book describes an easily applied language of mathematical modeling that uses boxes and arrows to develop very sophisticated algebraic statements of social and political phenomena. Graph algebra can be used to algebraically "flesh-out" even the most complicated and sophisticated of theories. Contains social science examples of graph algebra models: Social science readers can see many examples of how graph algebra can be used to model theories from a wide variety of substantive areas and disciplines. The book also describes how to estimate such models, and two examples are fully worked out. Explains linear and nonlinear model specifications using graph algebra from a social science perspective: Readers can move beyond simple linear regression models by using graph algebra. This text is ideal for use in graduate courses such as Statistical Modeling, Quantitative Methods, and Applied Mathematics.

目次

Series Editor's Introduction Acknowledgments 1. Systems Analysis Structure and Function An Overview of the Substantive Examples Found in Subsequent Chapters 2. Graph Algebra Basics Inputs, Outputs, and the Forward Path Feedback Loops and Mason's Rule An Example From Economics: The Keynesian Multiplier 3. Graph Algebra and Discrete-Time Linear Operators Delay and Advance Operators for Discrete Time Including an Additive Constant With Graph Algebra Difference and Summation Operators for Discrete Time An Estimated Example: Labor Union Membership 4. Working With Systems of Equations Richardson's Arms Race Model Using Graph Algebra Variations of Richardson's Arms Race Model An Estimated Example of a Multiple-Equation System With Nonlinear or Embedded Parameters: Richardson's Arms Race 5. Applying Graph Algebra to Continuous Time Using Graph Algebra With Continuous-Time Operators 6. Graph Algebra and Nonlinearity Nonlinear Filters The Logistic Function Placement Rules for Operators in Nonlinear Models Graph Algebra and Chaos Forced Oscillators 7. Working With Conditional Paths Logical and Decision Systems An Example of Democratic Transition 8. Systems, Shocks, and Stochasticity 9. Graph Algebra and Social Theory Systems and Equilibria References Index About the Author

「Nielsen BookData」 より

詳細情報

• NII書誌ID(NCID): BA82496852
• ISBN:
  • 9781412941099
• LCCN: 2007004811
• 出版国コード: us
• タイトル言語コード: eng
• 本文言語コード: eng
• 出版地: Thousand Oaks, Calif.
• ページ数/冊数: viii, 95 p.
• 大きさ: 22 cm
• 分類:
  • LCC : H61.25
  • DC22 : 300.1/5115
• 件名:
  • LCSH : Social sciences -- Mathematical models
  • LCSH : Graph theory
• 親書誌ID:
  • BA71788007