heavy-tailed distribution
Heavy-tailed distribution in the presence of dependence in insurance and finance
... Recently, for practical reasons, precise large deviations of dependent random variables have received a remarkable amount of attention. Kaas and Tang (2005) investigated pre- cise large deviation of a compound sum of ...
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A Novel Robust Rauch-Tung-Striebel Smoother Based on Slash and Generalized Hyperbolic Skew Student’s T-Distributions
... with heavy-tailed and/or skew noises. We propose to model heavy-tailed noises using a Gaussian scale mixture distribution and model heavy-tailed and skew noises using a ...
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The generalized double Lomax distribution with applications
... new heavy tailed distribution which is a generalization of the double Lomax distribution introduced by Bindu (2011) who applied it on IQ data, the proposed distribution was ...
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The Stock Returns Volatility based on the GARCH (1,1) Model: The Superiority of the Truncated Standard Normal Distribution in Forecasting Volatility
... The statistical analyses on the time series concentrated on the conditional first moment. The expanding role of risk and uncertainty in decision-making models and, in the meanwhile, changes in assessing the risk and ...
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Manpower Systems Operating under Heavy and Light Tailed Inter Exit Time Distributions
... 1 − B t = P T > t ~ c t θ − ν for t → ∞ (6) Where c and θ are positive constants. Obviously E T ( ) is finite and E T ( ) 2 = ∞ if 1 < < v 2 . The readers may refer to [11-13] and the references found there in ...
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Heavy Tailed Distributions of Effect Sizes in Systematic Reviews of Complex Interventions
... Although heavy-tailed distributions are known to arise in complex systems, the reason for this is not yet clear ...that heavy-tailed distributions may offer an efficient distribution ...
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Statistical modelling of the EUR/DZD returns with infinite variance distribution
... -stable distribution is better fitted to the returns than the Gaussian ...these heavy tailed distribution we evaluate the extreme risk considering two most often risk measures: the Value at ...
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LINKED OPEN GOVERNMENT DATA AS BACKGROUND KNOWLEDGE IN PREDICTING FOREST FIRE
... the heavy tailed distribution of the packet inter-arrival time, which is a result of the heavy tailed distribution of packet size of the traffic ...of heavy-tailed ...
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Double Penalized Quantile Regression in Partially Linear Models
... It is very important to note that many of those methods are closely related to the classical least squares me- thod. It is well known that the least squares method is not robust and can produce large bias when there are ...
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The Inverted Exponentiated Gamma Distribution: A Heavy-Tailed Model with Upside Down Bathtub Shaped Hazard Rate
... lifetime distribution called as IEGD and study its related distributional ...proposed distribution belongs to the inverted family of distributions and shows the UBT type hazard rate and is the member of ...
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Modeling the degree distributions of heavy-tailed networks by generalized Lomax models
... power-law distribution [8], [6], ...probability distribution P (x) ∝ x −α where, the parameter α is a positive constant and is known as the tail-index or shape parameter of the ...power-law ...
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On convergence of 1D Markov diffusions to heavy-tailed invariant density
... or distribution known up to a constant multiplier – a normalizing constant – how to construct a (Markov) process which would have this density as a (unique) invariant one and which would converge to this invariant ...
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Study on the Robust Wavelet Threshold Technique for Heavy-tailed Noises
... Gaussian distribution, but a heavy-tailed noise model ...nominal distribution has heavier than exponential tails [11]. For heavy-tailed noise has more outliers than Gaussian ...
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On uniqueness of moving average representations of heavy tailed stationary processes
... Provided that such a process exists, an important issue is the uniqueness of the MA represen- tation in (1). Uniqueness of the linear representation of non-Gaussian i.i.d. processes plays an important role in time ...
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Improved estimators of extreme Wang distortion risk measures for very heavy tailed distributions
... These new estimators, for all their improved properties as far as variability is concerned, should be expected to suffer from finite-sample bias issues, since they are in fact sample counterparts of a different quantity ...
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Least squares estimation for GARCH (1,1) model with heavy tailed errors
... following cases: i) in the presence of heavy tailed or skewed error distributions ii) when the volatility persistence is close to unity. It is important to note that both these features typically occur in ...
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Impact of Different Random Initializations on Generalization Performance of Extreme Learning Machine
... 3. The mostly-used Uniform distribution cannot bring about the better testing accuracy for ELM. The order of testing accuracy of Uniform distribution is 16 in Fig. 1-(b). The distributions with light tail, ...
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Heavy-tailed distributions : data, diagnostics, and new developments
... find heavy tailed phenomena all around ...of heavy tailed phenomena would render our traditional statistical tools useless at best, dangerous at ...
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Stochastic daily precipitation model with a heavy-tailed component
... (GP distribution) approaches, and allows modeling of the location, scale and shape parame- ters of the GEV distributions as functions of time-dependent covariates in order to account for non-stationarity ...the ...
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Local Explosion Modelling by Noncausal Process
... of heavy-tailed noncausal linear AR(1) processes that do not admit a causal linear AR representation, and to under- stand their potential usefulness in ...transition distribution in direct time ...
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