A Markov Chain based method for generating long-range dependence

نویسندگان

  • Richard G. Clegg
  • Maurice Dodson
چکیده

This paper describes a model for generating time series which exhibit the statistical phenomenon known as long-range dependence (LRD). A Markov modulated process based on an infinite Markov chain is described. The work described is motivated by applications in telecommunications where LRD is a known property of time series measured on the Internet. The process can generate a time series exhibiting LRD with known parameters and is particularly suitable for modeling Internet traffic because the time series is in terms of ones and zeros, which can be interpreted as data packets and interpacket gaps. The method is extremely simple, both computationally and analytically, and could prove more tractable than other methods described in the literature.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Modeling Video Traffic in the Wavelet Domain

A significant discovery from this work is that although video traffic has complicated shortand longrange dependence in the time domain, the corresponding wavelet coefficients are no longer long-range dependent in the wavelet domain. Therefore, a “short-range” dependent process can be used to model video traffic in the wavelet domain. In this work, we develop such wavelet models for VBR video tr...

متن کامل

COMPARISON ABILITY OF GA AND DP METHODS FOR OPTIMIZATION OF RELEASED WATER FROM RESERVOIR DAM BASED ON PRODUCED DIFFERENT SCENARIOS BY MARKOV CHAIN METHOD

Planning for supply water demands (drinkable and irrigation water demands) is a necessary problem. For this purpose, three subjects must be considered (optimization of water supply systems such as volume of reservoir dams, optimization of released water from reservoir and prediction of next droughts). For optimization of volume of reservoir dams, yield model is applied. Reliability of yield mod...

متن کامل

Bayesian Methods for Change-point Detection in Long-range Dependent Processes

We describe a Bayesian method for detecting structural changes in a long-range dependent process. In particular, we focus on changes in the long-range dependence parameter, d, and changes in the process level, μ. Markov chain Monte Carlo methods are used to estimate the posterior probability and size of a change at time t, along with other model parameters. A time-dependent Kalman filter approa...

متن کامل

Tra c in The Wavelet

| A signiicant discovery from this work is that although video traac has complicated short-and long-range dependence in the time domain, the corresponding wavelet coeecients are no longer long-range dependent in the wavelet domain. Therefore, a \short-range" dependent process can be used to model video traac in the wavelet domain. In this work, we develop such wavelet models for VBR video traac...

متن کامل

Modeling Common Long-range Dependence in Levels or Volatilities using Markov Chain Monte Carlo Methods

We present a sampling-based Bayesian approach for modeling and forecasting a common factor time series model in which the common components are long-range dependent. The Gibbs sampling framework allows us to use a less computationally demanding ARMA model to approximate the common long-range dependent behavior in the sampling algorithm; we then adjust for the approximation using importance samp...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Physical review. E, Statistical, nonlinear, and soft matter physics

دوره 72 2 Pt 2  شماره 

صفحات  -

تاریخ انتشار 2005