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Determination of the Model Parameters from Empirical Data

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Quantitative Sociodynamics

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Abstract

After the model parameters have been determined, a sensitivity analysis should be carried out. A test for the significance of the model parameters normally allows a model reduction. Furthermore, from the viewpoint of interpretation it is of interest on which factors the utility and distance functions of the considered behavioural changes depend. A corresponding decomposition with respect to explanatory variables is possible by means of a regression analysis in connection with a factor analysis or, alternatively, a ranking regression analysis. This is especially important for the prognosis of the future behaviour of the investigated system. Examples for the decomposition of utility functions into interpretable contributions will be discussed for purchase pattern and voting behaviour.

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Notes

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    This section can be omitted during a first reading.

References

  1. Aguda BD, Larter R, Clarke BL (1989) Dynamic elements of mixed-mode oscillations and chaos in a peroxidase-oxidase model network. J Chem Phys 90(8):4168–4175

    Article  Google Scholar 

  2. Beightler CS, Phillips DT, Wilde DJ (1979) Foundations of optimization, 2nd edn. Prentice-Hall, Englewood Cliffs, NJ, pp 220–223, 228–233

    Google Scholar 

  3. Burns J (1973) Application of control theory to system dynamics models of social systems. PhD thesis, Purdue University

    Google Scholar 

  4. Dinkel RH (1989) Landtagswahlen unter dem Einfluß der Bundespolitik: Die Erfahrungen der letzten Legislaturperioden. In: Falter JW, Rattinger H, Troitzsch KG (eds) Wahlen und politische Einstellungen. Lang, Frankfurt/Main

    Google Scholar 

  5. Eiselt HA, Pederzoli G, Sandblom C-L (1987) Continuous optimization models, Chap. 2.2.1: The gradient (steepest descent) method. De Gruyter, Berlin

    Google Scholar 

  6. Forsythe GE, Malcolm MA, Moler CB (1977) Computer methods for mathematical computations. Prentice-Hall, Englewood Cliffs, NJ

    MATH  Google Scholar 

  7. Freund JE (1988) Modern elementary statistics, 7th edn. Prentice-Hall, Englewood Cliffs, NJ

    Google Scholar 

  8. Freund JE (1992) Mathematical statistics, 5th edn. Prentice-Hall, Englewood Cliffs, NJ

    MATH  Google Scholar 

  9. Gelb A (ed) (1974) Applied optimal estimation, Chap. 6.3: Nonlinear least-squares estimation. MIT Press, Cambridge, MA

    Google Scholar 

  10. Granger CWJ, Newbold P (1977) Forecasting economic time series. Academic Press, New York, NY

    Google Scholar 

  11. Johnson RA, Wichern DW (1988) Applied multivariate statistical analysis, 2nd edn. Prentice Hall, Englewood Cliffs, NJ

    MATH  Google Scholar 

  12. Kendall SM (1976) Time-series, 2nd edn. Griffin, London

    Google Scholar 

  13. Kruskal JB, Wish M (1978) Multidimensional scaling. Sage, Beverly Hills, CA

    Google Scholar 

  14. Moore DS, McCabe GP (1989) Introduction to the practice of statistics. Freeman, New York, NY

    MATH  Google Scholar 

  15. Osgood CE, Suci GJ, Tannenbaum PH (1957) The measurement of meaning. University of Illinois Press, Urbana, IL

    Google Scholar 

  16. Reiner R, Munz M (1990) Ranking regression analysis of spatiotemporal variables. Environ Plan A 22:507–526

    Article  Google Scholar 

  17. Stübel G (1975) Sensitivity model generator as a tool for automatic credibility test of continuous system simulation. In: Proceedings of the 1975 summer simulation conference, San Francisco, pp 1189–1197

    Google Scholar 

  18. Theil H (1958) Economic forecasts and policy. North-Holland, Amsterdam, pp 31ff

    Google Scholar 

  19. Weidlich W, Haag G (eds) (1988) Interregional migration. Springer, Berlin

    Google Scholar 

  20. Young FW, Hamer RM (1987) Multidimensional scaling: history, theory, and applications. Lawrence Erlbaum Associates, Hillsdale, NJ

    Google Scholar 

  21. Zwicker E (1981) Simulation und Analyse dynamischer Systeme in den Wirtschafts- und Sozialwissenschaften. De Gruyter, Berlin, pp 444ff

    Google Scholar 

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Authors and Affiliations

  1. ETH Zurich, Swiss Federal Institute of Technology, CLU E 1, Clausiusstrasse 50, 8092, Zurich, Switzerland

    Prof. Dr. Dirk Helbing (Chair of Sociology, in particular of Modeling and Simulation)

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  1. Prof. Dr. Dirk Helbing
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Correspondence to Dirk Helbing .

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Helbing, D. (2010). Determination of the Model Parameters from Empirical Data . In: Quantitative Sociodynamics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11546-2_13

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