Skip to main content
Log in

Estimation of the Parameters of Fractional-Stable Laws by the Method of Minimum Distance*

  • Published:
Journal of Mathematical Sciences Aims and scope Submit manuscript

Algorithm for statistical estimation of the parameters of fractional-stable distributions is described in this article. This algorithm is constructed on the basis of the method of distance minimization between the empirical and theoretical distributions. As the distance between the two distributions, the χ distance is considered. The main difficulty in dealing with fractional-stable distributions is the absence of explicit expressions for the probability density function. That is why the theoretical density is estimated by the histogram method. The results of the test calculations and the results of the estimation of the quadratic deviation are presented. The results obtained by this estimator are compared with the results obtained by the method of moments. An example of the use of the estimator for the approximation of the experimental data obtained in the investigation of gene expression by RNA sequencing technology is given as well. It is shown that the probability density function of the gene expression in a wide-enough domain can be described by fractional-stable distributions.

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. C. R. Dance and E. E. Kuruglu, “Estimation of the Parameters of Skewed a-Stable Distributions,” Technical Report (1999).

  2. E. E. Kuruoglu, “Density parameter estimation of skewed amp;alpha;-stable distributions,” IEEE Trans. Signal Process., 49, No. 10, 2192–2201 (2001).

    Article  MathSciNet  Google Scholar 

  3. V. M. Zolotarev, “Statistical estimates of the parameters of stable laws,” Math. Stat.: Banach Center Publ., 6, 359–376 (1980).

  4. V. M. Zolotarev, One-dimensional stable Distributions. Amer. Mat. Soc., Providence (1986).

    MATH  Google Scholar 

  5. V. E. Bening, V. Y. Korolev, V. N. Kolokoltsov, V. V. Uchaikin, V. V. Saenko, and V. M. Zolotarev, “Estimation of parameters of fractional stable distributions,” J. Math. Sci., 123, No. 1, 3722 – 3732 (2004).

    Article  MathSciNet  MATH  Google Scholar 

  6. A. S. Paulson, E. W. Holcomb, and R. A. Leitch, “The estimation of the parameters of the stable laws,” Biometrika, 62, No. 1, 163–170 (1975).

  7. G. J. Worsdale, “The Estimation of the Symmetric Stable Distribution Parameters,” Metrika, 23, No. 1, 55–63 (1981).

  8. B.Wade Brorsen and S. R. Yang, “Maximum Likelihood Estimates of Symmetric Stable Distribution Parameters,” Commun. Stat. Simul. Comput., 19, 1459–1464 (1990).

    Article  MATH  Google Scholar 

  9. J. P. Nolan, “Maximum likelihood estimation and diagnostics for stable distributions,” L´evy Processes: Theory and Applications, Springer, New York, 379–400 (2001).

  10. N. Ravishanker, “Monte Carlop EM Estimation for Stable Distribution,” in: Heavy Tails’99, (1999), p. Tails45.

  11. V. V. Saenko, “Maximum likelihood algorithm for approximation of local fluctuational fluxes at the plasma periphery by fractional stable distributions,” arXivID: 1209.2297 (2012).

  12. V. V. Uchaikin and V. V. Saenko, “Simulation of random vectors with isotropic fractional stable distributions and calculation of their probability density function,” J. Math. Sci., 112, No. 2, 4211 – 4228 (2002).

    Article  MathSciNet  MATH  Google Scholar 

  13. E. F. Fama and R. Roll, “Parameter estimates for symmetric stable distributions,” J. Am. Stat. Assoc., 66, No. 334, 331–338 (1971).

    Article  MATH  Google Scholar 

  14. S. Maymon, J. Friedman, E. Fisher, and H. Messer-Yaron, “Estimation of the Parameters of a Stable Distribution Based on Order Statistics,” in: Heavy Tails’99, (1999), p. Tails37.

  15. V. N. Kolokoltsov, V. Y. Korolev, and V. V. Uchaikin, “Fractional Stable Distributions,” J. Math. Sci., 105, No. 6, pp. 2569–2576 (2001).

    Article  MathSciNet  MATH  Google Scholar 

  16. B. Bunday, Basic Optimization Methods, Hodder Arnold (1984).

  17. H. R. Ueda, S. Hayashi, S. Matsuyama, T. Yomo, S. Hashimoto, S. A. Kay, J. B. Hogenesch, and M. Iino, “Universality and flexibility in gene expression from bacteria to human.,” Proc. Natl. Acad. Sci. USA, 101, 3765–3769 (2004).

    Article  Google Scholar 

  18. L. S. Liebovitch, V. K. Jirsa, and L. A. Shehadeh, “Structure of genetic regulatory networks: evidence for scale free networks,” in Complexus Mundi - Emergent Patterns in Nature, World Scientific Publishing Co. Pte. Ltd., Singapore (2006), pp. 1–8.

    Google Scholar 

  19. C. Furusawa and K. Kaneko, “Zipfs Law in Gene Expression,” Phys. Rev. Lett., 90, 8–11 (2003).

    Article  Google Scholar 

  20. V. A. Kuznetsov, G. D. Knott, and R. F. Bonner, “General statistics of stochastic process of gene expression in eukaryotic cells,” Genetics, 161, 1321–1332 (2002).

    Google Scholar 

  21. D. C. Hoyle, M. Rattray, R. Jupp, and A. Brass, “Making sense of microarray data distributions,” Bioinformatics (Oxford, England), 18, 576–84 (2002).

  22. C. Lu and R. D. King, “An investigation into the population abundance distribution of mRNAs, proteins, and metabolites in biological systems,” Bioinformatics (Oxford, England), 25, 2020–2027 (2009).

  23. J. M. Chambers, C. L. Mallows, and B. W. Stuck, “A method for simulating stable random variables,” J. Am. Stat. Assoc., 71, No. 354, 340–344 (1976).

    Article  MathSciNet  MATH  Google Scholar 

  24. M. Kanter, “Stable Densities Under Change of Scale and Total Variation Inequalities,” Ann. Probab., 3, No. 4, 697–707 (1975).

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to V. V. Saenko.

Additional information

*The work was supported by the Ministry of Education and Science of the Russian Federation (grant No 6.1617.2014/K)

Proceedings of the XXXII International Seminar on Stability Problems for Stochastic Models, Trondheim, Norway, June 16–21, 2014.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Saenko, V.V. Estimation of the Parameters of Fractional-Stable Laws by the Method of Minimum Distance*. J Math Sci 214, 101–114 (2016). https://doi.org/10.1007/s10958-016-2760-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10958-016-2760-y

Keywords

Navigation