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Dampening Effect




Dampening is the gradual reduction the amplitudes of Oscillation s, which can be observed, e.g., when plucking string of a musical instrument. In the physical sciences, this effect is also called Damping .


DAMPENING EFFECT IN TIME SERIES ANALYSIS


The analysis of time series within the interactive computer environment is part of the recent theoretical and methodological developments within data analysis pertaining to social science research which brings the ideal of causal modeling within the grasp of social scientists. During the Time Series analysis by alternating autocorrelation analysis with differencing of the successive intervals, the resulting trend is subject to the dampening effect which beomes progressively more pronounced towart the end of the series, as shown in Fig. 1. By using an algorithm for the autocorrelation part of the analysis by Krus and Ko (1983), this dampening effect is filtered out (cf., Fig.2). This is especially advantageous when one contemplates the analysis of complicated or lengthy secular trends.


REFERENCES


  • Denton, F. H. and Phillips, W. Some patterns in the history of violence. Journal of Conflict Resolution, 1968, 12, 182-15.

  • Krus, D. J. & Blackman, H. S. (1980) Time scale factor as related to theories of societal change. Psychological Reports, 46, 95-102. (Request reprint) .

  • Krus, D.J., & Ko, H.O. (1983) Algorithm for autocorrelation analysis of secular trends. Educational and Psychological Measurement, 43, 821-828. (Request reprint).

  • Krus, D.J., Nelsen, E.A. & Webb, J.M. (1998) Recurrence of war in classical East and West civilizations. Psychological Reports, 83, 139-143.


  • Krus, D. J. and Ceurvorst, R. W. Computed assisted construction of variable norms. Educational and Psychological Measurement, 1978. 38, 815-818.


  • Makridakis, S. and Wheelwright, S. C. Interactive forecasting: Univariate and multivariate methods. (2nd ed.). San Francisco: Holden-Day, 1978.


  • McCleary, R. and Hay, R. A. Applied time series analysis for the social sciences. Beverly Hills, Ca: Sage, 1980.


  • Moyal, J. E. The distribution of wars in time. Journal of the Royal Statistical Society, 1949, 112, 446-458.


  • Southworth, R. W. Autocorrelation and spectral analysis. In A. Ralston and H. S. Wilf (Eds.) Mathematical methods for digital computers. New York: Wiley, 1960.



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