VTeX: Solutions for Science Publishing logo


  • List of journals
  • Browse subjects
  • About Publisher
  • Help
  • Sitemap
Login Register

  1. Home
  2. Journals
  3. MSTA
  4. Issues
  5. Volume 2, Issue 4 (2015)
  6. Tempered Hermite process

Modern Stochastics: Theory and Applications*

Submit your article Information Become a Peer-reviewer VTeX
  • Article info
  • Full article
  • Related articles
  • More
    Article info Full article Related articles

Tempered Hermite process
Volume 2, Issue 4 (2015), pp. 327–341
Farzad Sabzikar  

Authors

 
Placeholder
https://doi.org/10.15559/15-MSTA34
Pub. online: 25 September 2015      Type: Research Article      Open accessOpen Access

Received
9 July 2015
Revised
7 September 2015
Accepted
11 September 2015
Published
25 September 2015

Abstract

A tempered Hermite process modifies the power law kernel in the time domain representation of a Hermite process by multiplying an exponential tempering factor $\lambda >0$ such that the process is well defined for Hurst parameter $H>\frac{1}{2}$. A tempered Hermite process is the weak convergence limit of a certain discrete chaos process.

References

[1] 
Abramowitz, M., Stegun, I.: Handbook of Mathematical Functions, 9th edn. Dover, New York (1965)
[2] 
Avram, F., Taqqu, M.S.: Noncentral limit theorems and Appell polynomials. Ann. Probab. 15, 767–775 (1987). MR0885142. doi:10.1214/aop/1176992170
[3] 
Bai, S., Taqqu, M.S.: Generalized Hermite processes, discrete chaos and limit theorems. Stoch. Process. Appl. 124, 1710–1739 (2014). MR3163219. doi:10.1016/j.spa.2013.12.011
[4] 
Baricz, Á.: Bounds for modified Bessel functions of the first and second kinds. Proc. Edinb. Math. Soc. 53, 575–599 (2010). MR2720238. doi:10.1017/S0013091508001016
[5] 
Billingsley, P.: Convergence of Probability Measures. Wiley, New York (1968). MR0233396
[6] 
Brockwell, P.J., Davis, R.A.: Time Series: Theory and Methods, 2nd edn. Springer, New York (1991). MR1093459. doi:10.1007/978-1-4419-0320-4
[7] 
Davydov, Y.: The invariance principle for stationary processes. Teor. Veroâtn. Primen. 15, 498–509 (1970). MR0283872
[8] 
Dobrushin, R.L., Major, P.: Non-central limit theorems for non-linear functionals of Gaussian fields. Z. Wahrscheinlichkeitstheor. Verw. Geb. 50, 27–52 (1979). MR0550122. doi:10.1007/BF00535673
[9] 
Embrechts, P., Maejima, M.: Selfsimilar Processes. Princeton Series in Applied Mathematics. Princeton University Press, Princeton, NJ (2002). MR1920153
[10] 
Friedlander S., K., Topper, L.: Turbulence: Classical Papers on Statistical Theory. Interscience Publishers, New York (1962). MR0118165
[11] 
Gaunt, R.E.: Inequalities for modified Bessel functions and their integrals. J. Math. Anal. Appl. 420, 373–386 (2014). MR3229830. doi:10.1016/j.jmaa.2014.05.083
[12] 
Giraitis, L., Koul, H.L., Surgailis, D.: Large Sample Inference for Long Memory Processes (2012). World Scientific Publishing Company Incorporated. MR2977317. doi:10.1142/p591
[13] 
Gradshteyn, I.S., Ryzhik, I.M.: Table of Integrals and Products, 6th edn. Academic Press (2000). MR1773820
[14] 
Kolmogorov, A.N.: Wiener spiral and some other interesting curves in Hilbert space. Dokl. Akad. Nauk SSSR 26, 115–118 (1940)
[15] 
Lamperti, J.: Semi-stable stochastic processes. Trans. Am. Math. Soc. 104, 62–78 (1962). MR0138128. doi:10.1090/S0002-9947-1962-0138128-7
[16] 
Maejima, M.: On a class of self-similar processes. Z. Wahrscheinlichkeitstheor. Verw. Geb. 62, 235–245 (1983). MR0688988. doi:10.1007/BF00538799
[17] 
Meerschaert, M.M., Sabzikar, F.: Tempered fractional Brownian motion. Stat. Probab. Lett. 83(10), 2269–2275 (2013). MR3093813. doi:10.1016/j.spl.2013.06.016
[18] 
Meerschaert, M.M., Sabzikar, F.: Stochastic integration with respect to tempered fractional Brownian motion. Stoch. Process. Appl. 124, 2363–2387 (2014). MR3192500. doi:10.1016/j.spa.2014.03.002
[19] 
Meerschaert, M.M., Sikorskii, A.: Stochastic Models for Fractional Calculus. De Gruyter, Berlin/Boston (2012). MR2884383
[20] 
Meerschaert, M.M., Sabzikar, Phanikumar M. S, F., Zeleke, A.: Tempered fractional time series model for turbulence in geophysical flows. J. Stat. Mech. Theory Exp. 14, P09023 (2014) (13 pp.). doi:10.1088/1742-5468/2014/09/P09023
[21] 
Peccati, G., Taqqu, M.S.: Wiener Chaos: Moments, Cumulants and Diagrams: A survey with Computer Implementation. Springer (2011). MR2791919. doi:10.1007/978-88-470-1679-8
[22] 
Pipiras, V., Taqqu, M.: Convergence of weighted sums of random variables with long range dependence. Stoch. Process. Appl. 90, 157–174 (2000). MR1787130. doi:10.1016/S0304-4149(00)00040-5
[23] 
Pipiras, V., Taqqu, M.: Integration questions related to fractional Brownian motion. Probab. Theory Relat. Fields 118, 251–291 (2000). MR1790083. doi:10.1007/s440-000-8016-7
[24] 
Sabzikar, Meerschaert M. M, F., Chen, J.: Tempered fractional calculus. J. Comput. Phys. 293, 14–28 (2015). MR3342453. doi:10.1016/j.jcp.2014.04.024
[25] 
Samorodnitsky, G., Taqqu, M.: Stable Non-Gaussian Random Processes: Stochastic Models with Infinite Variance. Chapman & Hall (1994). MR1280932
[26] 
Taqqu, M.S.: Convergence of integrated processes of arbitrary Hermite rank. Probab. Theory Relat. Fields 50(1), 53–83 (1979). MR0550123. doi:10.1007/BF00535674
[27] 
Whitt, W.: Stochastic-Process Limits. Springer, New York (2002). MR1876437

Full article Related articles PDF XML
Full article Related articles PDF XML

Copyright
© 2015 The Author(s). Published by VTeX
by logo by logo
Open access article under the CC BY license.

Keywords
Discrete chaos limit theorem Wiener–Itô integral Fourier transform

MSC2010
60F17 60G23 60G20

Metrics
since February 2017
0

Article info
views

0

Full article
views

3

PDF
downloads

7

XML
downloads

Export citation

Copy and paste formatted citation
Placeholder

Download citation in file


Share


RSS

  • About Publisher
Powered by PubliMill  •  Privacy policy