Skip to main content
Log in

The Weierstrass–Mandelbrot Process Revisited

  • Published:
Journal of Statistical Physics Aims and scope Submit manuscript

Abstract

We derive a functional central limit theorem for quasi-Gaussian processes. In particular, we prove that the limit of the Mandelbrot–Weierstrass process is a complex fractional Brownian motion.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

REFERENCES

  1. M. Ausloss and D. H. Berman, A multivariate Weierstrass-Mandelbrot function, Proc. R. Soc. Lond. A 400:331-350 (1985).

    Google Scholar 

  2. M. V. Berry and Z. V. Lewis, On the Weierstrass-Mandelbrot fractal function, Proc. R. Soc. Lond. A 370:459-484 (1980).

    Google Scholar 

  3. J. Chu, Conditional fractal simulation, sequential indicator simulation, and interactive variogram simulation, PhD Dissertation, 1993.

  4. I. S. Gradshteyn and I. M. Ryzhik, Tables of Integrals, Series and Products [translation] (Academic Press, New York, 1980).

    Google Scholar 

  5. T. A. Hewett and R. A. Behrens, Conditional simulation of reservoir heterogeneity with fractals, SPE Reservoir Research (1989).

  6. T. Kawata, Fourier Analysis in Probability Theory (Academic Press, New York, 1972).

    Google Scholar 

  7. V. Klemeś, The Hurst phenomenon: A puzzle? Water Resources Research 10(4):675-688 (1974).

    Google Scholar 

  8. A. Kolmogorov, Wienersche Spiralen und einige andere interessante Kurven im Hilbertischen Raum, Doklady Acad. Sci. URSS, New Series 26:115-118, 1940.

    Google Scholar 

  9. G. Korvin, Fractal Models in the Earth Sciences (Elsevier, 1992).

  10. A. J. Lawrance and N. T. Kottegoda, Stochastic modelling of riverflow time series, J. R. Statist. Soc. A 140:1-31 (1977).

    Google Scholar 

  11. A. W. Lo, Long term memory in stock market prices, Econometrica 59(5):1279-1313 (1991).

    Google Scholar 

  12. Eugene Lukacs, Characteristic Functions, Second ed. (Hafner Publishing Co., New York, 1970).

    Google Scholar 

  13. J. Jacod and A. Shiryaev, Limit Theorems for Stochastic processes (Springer, 1987).

  14. B. Mandelbrot, Fractals: Form, Chance, and Dimension. (Freeman and Co., San Francisco, 1977).

    Google Scholar 

  15. B. Mandelbrot and J. Van Ness, Fractional Brownian motion, fractional noises and applications, SIAM Review 10:422-437 (1968).

    Google Scholar 

  16. B. Mandelbrot and J. R. Wallis, Noah, Joseph, and operational hydrology, Water Resources Research 4(5):909-918 (1968).

    Google Scholar 

  17. B. Mandelbrot and J. R. Wallis, Computer experiments with fractional Gaussian noises. Part 1, averages and variances, Water Resources Research 5(1):228-267 (1969).

    Google Scholar 

  18. B. Mandelbrot and J. R. Wallis, Robustness of the rescaled range R/S analysis in the measurement of noncyclic long run statistical dependence, Water Resources Research 5(5):967-988 (1969).

    Google Scholar 

  19. B. Mandelbrot and J. R. Wallis, Some long run properties of geophysical records, Water Resources Research 5(2):321-340 (1969).

    Google Scholar 

  20. F. J. Molz and G. K. Boman, A fractal based stochastic interpolation scheme in subsurface hydrology, Water Resources Research 29(11):3769-3774 (1993).

    Google Scholar 

  21. F. J. Molz, J. Szulga, and H. H. Liu, Fractional Brownian motion and fractional Gaussian noise in subsurface hydrology: A review of fundamental properties, Water Resources Research 33(10):2273-2286 (1997).

    Google Scholar 

  22. V. Pipiras and M. S. Taqqu, Convergence of the Weierstrass-Mandelbrot process to fractional Brownian motion, Fractals 8(4):369-384 (2000).

    Google Scholar 

  23. S. T. Rachev, Probability Metrics and the Stability of Stochastic Models, Series in Probability and Mathematical Statistics: Applied Probability and Statistics (Wiley, Chichester, 1991).

    Google Scholar 

  24. W. Rümelin, Simulation of fractional Brownian Motion, in Fractals in the Fundamental and Applied Sciences, Proceedings of the First IFIP Conference, Lisbon 1990, H.-O. Peitgen, J. M. Henriques and L. F. Penedo, ed. (North-Holland Publishing Co., Amsterdam, 1991).

    Google Scholar 

  25. J. Szulga, Introduction to Random Chaos (Chapman & Hall, 1998).

  26. J. Szulga, Hausdorff dimension of Weierstrass-Mandelbrot process, Auburn University Preprint, 2001.

  27. J. Szulga and F. J. Molz, On simulating fractional Brownian motion, in High Dimensional Probability II, E. Giné, et al., ed. (Birkhauser, Boston, 2000), pp. 377-387.

    Google Scholar 

  28. D. L. Turcotte, Fractals in geology and geophysics, PAGEOPH 131(1/2):171-196 (1989).

    Google Scholar 

  29. R. F. Voss, Voss, Random fractals: self-affinity in noise, music, mountains, and clouds, Fractals in Physics (Vence, 1989) 38(1-3):362-371 (1989).

    Google Scholar 

  30. A. M. Yaglom, Correlation theory of processes with random stationary increments, Trans. Amer. Math. Soc. 8:87-141 (1958).

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Szulga, J., Molz, F. The Weierstrass–Mandelbrot Process Revisited. Journal of Statistical Physics 104, 1317–1348 (2001). https://doi.org/10.1023/A:1010422315759

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1010422315759

Navigation