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Constraint Analysis in Structure Modelling: A Probabilistic Approach

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Part of the book series: NATO Conference Series ((SYSC,volume 5))

Abstract

Broekstra [1] introduced the use of information theoretic quantities in structure modelling. The basic idea is that in any statistically analysable system of variables, the effects of some variables on others are reflected statistically as non-independence of the variables involved. This deviation from independence is indicated by the term “constraint.”

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References

  1. G. Broekstra, Structure Modelling: “A Constraint (Information) Analytic Approach,” forthcoming 1977.

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  2. W. A. Wallis and H. V. Roberts, Statistics: A New Approach. The Free Press, New York, 1965.

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  7. R. C. Conant, “Laws of Information Which Govern Systems,” IEEE Transactions on Systems, Man, and Cybernetics, 6, No. 4, April 1976.

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  8. H. M. Blalock, “Four-Variable Causal Models and Partial Correlations,” The American Journal of Sociology, 68, pp. 182–194, 1962.

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  9. F. A. Graybill, An Introduction to Linear Statistical Models, McGraw-Hill, New York, 1961.

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  10. A. P. J. Abrahamse, Constraint Analysis on Structure Modelling: A Probabilistic Approach, Report R/77/26, Graduate School of Management, Delft.

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© 1978 Springer Science+Business Media New York

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Abrahamse, A.P.J. (1978). Constraint Analysis in Structure Modelling: A Probabilistic Approach. In: Klir, G.J. (eds) Applied General Systems Research. NATO Conference Series, vol 5. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-0555-3_8

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  • DOI: https://doi.org/10.1007/978-1-4757-0555-3_8

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4757-0557-7

  • Online ISBN: 978-1-4757-0555-3

  • eBook Packages: Springer Book Archive

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