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141
2004): “Subsampling the mean of heavytailed dependent observations
 Journal of Time Series Analysis
"... We establish the validity of subsampling confidence intervals for the mean of a dependent series with heavytailed marginal distributions. Using point process theory, we study both linear and nonlinear GARCHlike time series models. We propose a datadependent method for the optimal block size selec ..."
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Cited by 3 (0 self)
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We establish the validity of subsampling confidence intervals for the mean of a dependent series with heavytailed marginal distributions. Using point process theory, we study both linear and nonlinear GARCHlike time series models. We propose a datadependent method for the optimal block size
Analysis, Modeling and Generation of SelfSimilar VBR Video Traffic
, 1994
"... We present a detailed statistical analysis of a 2hour long empirical sample of VBR video. The sample was obtained by applying a simple intraframe video compression code to an action movie. The main findings of our analysis are (1) the tail behavior of the marginal bandwidth distribution can be accu ..."
Abstract

Cited by 548 (6 self)
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for VBR video and present an algorithm for generating synthetic traffic. Tracedriven simulations show that statistical multiplexing results in significant bandwidth efficiency even when longrange dependence is present. Simulations of our source model show longrange dependence and heavytailed marginals
Estimating LongRange Dependence in Impulsive Traffic Flows
 Proc. of ICASSP 01
, 2001
"... Traffic flow in highspeed data network systems is often impulsive and longrange dependent. Impulsiveness implies a heavytailed marginal distribution,... ..."
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Cited by 2 (2 self)
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Traffic flow in highspeed data network systems is often impulsive and longrange dependent. Impulsiveness implies a heavytailed marginal distribution,...
Tail approximation for credit risk portfolios with heavytailed risk factors
 Journal of Risk
, 2006
"... We consider a portfolio credit risk model in the spirit of CreditMetrics [15]. The multivariate normally distributed underlying risk factors in that model are replaced by more general multivariate elliptical factors with heavytailed marginals, introducing taildependence. We consider a fullscale ..."
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Cited by 4 (0 self)
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We consider a portfolio credit risk model in the spirit of CreditMetrics [15]. The multivariate normally distributed underlying risk factors in that model are replaced by more general multivariate elliptical factors with heavytailed marginals, introducing taildependence. We consider a full
unknown title
"... ⋆ Financial processes are known to exhibit a combination of properties including semiheavytailed marginal distributions, short or longrange dependence, volatility and scaling. Current models of their nonGaussian behaviour relies ..."
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⋆ Financial processes are known to exhibit a combination of properties including semiheavytailed marginal distributions, short or longrange dependence, volatility and scaling. Current models of their nonGaussian behaviour relies
Tdistributed random fields: A parametric model for heavytailed welllog data
 Math. Geol
, 2006
"... Histograms of observations from spatial phenomena are often found to be more heavytailed than Gaussian distributions, which makes the Gaussian random field model unsuited. A Tdistributed random field model with heavytailed marginal probability density functions is defined. The model is a general ..."
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Cited by 7 (2 self)
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Histograms of observations from spatial phenomena are often found to be more heavytailed than Gaussian distributions, which makes the Gaussian random field model unsuited. A Tdistributed random field model with heavytailed marginal probability density functions is defined. The model is a
HeavyTailed Processes for Selective Shrinkage
"... Heavytailed distributions are frequently used to enhance the robustness of regression and classification methods to outliers in output space. Often, however, we are confronted with “outliers ” in input space, which are isolated observations in sparsely populated regions. We show that heavytailed s ..."
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that selective shrinkage occurs, provided the marginals of the heavytailed process have sufficiently heavy tails. The analysis is complemented by experiments on biological data which indicate significant improvements of estimates in sparse regions while producing competitive results in dense regions. Gaussian
Limit Theory For Bilinear Processes With Heavy Tailed Noise
 Ann. Appl. Probab
, 1995
"... . We consider a simple stationary bilinear model X t = cX t\Gamma1 Z t\Gamma1 + Z t ; t = 0; \Sigma1; \Sigma2; : : : generated by heavy tailed noise variables fZ t g. A complete analysis of weak limit behavior is given by means of a point process analysis. A striking feature of this analysis is th ..."
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Cited by 56 (16 self)
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features such as long range dependence, nonlinearity and heavy tails. There are numerous data sets from the fields of telecommunications, finance and economics which appear to be compatible with the assumption of heavytailed marginal distributions. Examples include file lengths, cpu time to complete a
Highlevel dependence in time series models
, 2009
"... We present several notions of highlevel dependence for stochastic processes, which have appeared in the literature. We calculate such measures for discrete and continuoustime models, where we concentrate on time series with heavytailed marginals, where extremes are likely to occur in clusters. Su ..."
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Cited by 11 (4 self)
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We present several notions of highlevel dependence for stochastic processes, which have appeared in the literature. We calculate such measures for discrete and continuoustime models, where we concentrate on time series with heavytailed marginals, where extremes are likely to occur in clusters
HeavyTailed Process Priors for Selective Shrinkage
 Advances in Neural Information Processing Systems 23
, 2010
"... Heavytailed distributions are often used to enhance the robustness of regression and classification methods to outliers in output space. Often, however, we are confronted with “outliers ” in input space, which are isolated observations in sparsely populated regions. We show that heavytailed stocha ..."
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Cited by 3 (1 self)
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that selective shrinkage occurs when the marginals of the heavytailed process have sufficiently heavy tails. The analysis is complemented by experiments on biological data which indicate significant improvements of estimates in sparse regions while producing competitive results in dense regions. 1
Results 1  10
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141