Characterizing impulsive network traffic using truncated α-stable processes

Tang, Xiaolu; Ma, Meng; Ostry, Diethelm; Jiao, Bingli; Guo, Yuanzhi

doi:10.1109/lcomm.2009.12.091507

Cited by 7 publications

(1 citation statement)

References 6 publications

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“…Truncated stable random variables arise in many applied fields such as characterization of impulsive network traffic [47] and GARCH models and option pricing [22]. Some algorithms proposed in [27], [44], [43], [49], and [50] to simulate truncated stable random variables.…”

Section: Introductionmentioning

confidence: 99%

alphastable: An R Package for Modelling Multivariate Stable and Mixture of Symmetric Stable Distributions

Teimouri,

Torshizi,

Mohammadpour

et al. 2018

Preprint

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The family of stable distributions received extensive applications in many fields of studies since it incorporates both the skewness and heavy tails. In this paper, we introduce a package written in the R language called alphastable. The alphastable performs a variety of tasks including: 1-generating random numbers from univariate, truncated, and multivariate stable distributions. 2-computing the probability density function of univariate and multivariate elliptically contoured stable distributions, 3-computing the distribution function of univariate stable distributions, 4-estimating the parameters of univariate symmetric stable, univariate Cauchy, mixture of Cauchy, mixture of univariate symmetric stable, multivariate elliptically contoured stable, and multivariate strictly stable distributions. This package, as it will be shown, is very useful for modelling data in univariate and multivariate cases that arise in the fields of finance and economics.

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