Questions tagged [long-range-dependence]

Used for time series with long memory. Could also arise in spatial data.

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long-range dependence measure

Hurst exponent is a simple, powerful and widely used measure of a long-term memory of time series. What is are the disadvantages of this measure for checking long-range dependence in the series and ...
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Biased estimates of Hurst exponent in R/S analysis

I've used the standard R/S algorithm for estimating the Hurst exponent in Mathematica*, and tested it on fBm and fGn for $H\in\{0.05,0.1,\ldots,0.95\}$, generating 1000 time series for each $H$. The ...
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How small is too small to fit a reasonable long memory model?

When looking at papers about long memory they tend to analyze data sets whose length is in the thousands, see http://www.math.canterbury.ac.nz/~m.reale/pub/Reaetal2011.pdf for an example. My question ...
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Compare long range dependence among non-stationary multivariate time series'

I have 5 non-stationary multivariate time series' and I need to compare the "strength" of long range dependence among them. I have found many papers on long range dependence estimation (parametric, ...
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45 views

Verifying long-range dependency in multi-variate time series

I am fairly new to the area of time series and I am trying to understand the notion of long-range dependence in time series. My goal is to characterize the same in the case of multi-variate time ...
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Can processes with long range dependence be classified as stationary/non-stationary?

If my process has long range dependence (hurst exponent > 0.5 ) can it be concluded that it is stationary/non-stationary? How? Is there any correlation between Long range dependence and Stationarity?
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919 views

Why can't ARIMA model large lags and/or long range dependence?

ARIMA cannot model large lags (obtained from autocorrelation plot) and long range dependency (hurst exponent $H > 0.5$). Why is it so?
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228 views

Aggregate variance function and Hurst parameter

What is the aggregate variance method for estimating the value of Hurst exponent? How does it measure long range dependence?
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286 views

Simulating data with long range dependencies

I want to evaluate how well a recurrent neural network I've created captures long-range dependencies, and the effects altering the network have on this. I'm not entirely sure how I would go about ...
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163 views

ARFIMA covariance structure

I have a set of response processes (queue lengths in infinite server network). Using queue theory, I can numerically calculate response autocovariance structure, from the known service time ...
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1answer
443 views

Extreme Value Theory and heavy (long) tailed distributions

I'm analyzing data about which I have a strong suspicion that it is self-similar (Hurst parameter ranging from 0.60 to 0.78 depending on estimation method and sample sequence). I also observe high ...
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386 views

Examining correlation and long range dependence in time series data with strong diurnal effects [closed]

I have data sets of network traffic that exhibit strong diurnal effects making them non-stationary. One of the analysis that I want to run is to show correlation between days. If we chopped up the ...
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1answer
155 views

Minimum number of observations to determine long range dependency

What is the minimum number of observations to be considered in order to determine long range dependency? I'm trying to estimate Hurst parameter using R/S method. I've used SELFIS as well as R. ...
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550 views

Predicting long-memory processes

I'm working with a two-state process with $x_t$ in $\{1, -1\}$ for $t = 1, 2, \ldots$ The autocorrelation function is indicative of a process with long-memory, i.e. it displays a power law decay with ...