## Heavy Tail Modeling And Teletraffic Data (1997)

Venue: | Annals of Statistics |

Citations: | 54 - 4 self |

### BibTeX

@ARTICLE{Resnick97heavytail,

author = {Sidney I. Resnick},

title = {Heavy Tail Modeling And Teletraffic Data},

journal = {Annals of Statistics},

year = {1997},

volume = {25},

pages = {1805--1869}

}

### Years of Citing Articles

### OpenURL

### Abstract

. Huge data sets from the teletraffic industry exhibit many non-standard characteristics such as heavy tails and long range dependence. Various estimation methods for heavy tailed time series with positive innovations are reviewed. These include parameter estimation and model identification methods for autoregressions and moving averages. Parameter estimation methods include those of Yule-Walker and the linear programming estimators of Feigin and Resnick as well estimators for tail heaviness such as the Hill estimator and the qq-estimator. Examples are given using call holding data and inter-arrivals between packet transmissions on a computer network. The limit theory makes heavy use of point process techniques and random set theory. 1. Introduction Classical queuing and network stochastic models contain simplifying assumptions guaranteeing the Markov property and insuring analytical tractability. Frequently inter-arrivals and service times are assumed to be iid and typically underlyi...