Heavy-tailed distributions
Advances in the Modeling of Heavy-tailed Distributions
... encounter heavy-tailed distributions in actuarial or econometric applica- ...those distributions is that they only possess a finite number of moments, which curtails the applicability of ...
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Modeling of Insurance Data through Two Heavy Tailed Distributions: Computations of Some of Their Actuarial Quantities through Simulation from Their Equilibrium Distributions and the Use of Their Convolutions
... The paper has made an attempt to address the complex issue of evaluating the convolution of the Weibull and the Burr XII distributions. Further investigation is needed to identify if any method other than ...
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Heavy Tailed Distributions Generated by Randomly Sampled Gaussian, Exponential and Power Law Functions
... A simple stochastic mechanism that produces exact and approximate power-law distributions is presented. The model considers radially symmetric Gaussian, exponential and power-law func- tions in n = 1, 2, 3 ...
8
Improved estimators of extreme Wang distortion risk measures for very heavy tailed distributions
... using heavy-tailed distributions, which shall be the focus of this ...be heavy-tailed if its survival func- tion 1 − F, where F is the related cumulative distribution function, roughly ...
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Assessing The Relative Performance Of Heavy-Tailed Distributions: Empirical Evidence From The Johannesburg Stock Exchange
... of heavy tailed distributions to capture the anomalies embedded in the returns data of South African market, but it will also provide a glimpse into a cross-comparison of the performance of these ...
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Generalized independent low rank matrix analysis using heavy tailed distributions for blind source separation
... more heavy-tailed ...Gaussian distributions as special cases and has been used to model audio sources [36, ...Gaussian distributions are a part of the α-stable dis- tribution family [41], ...
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Heavy Tailed Distributions of Effect Sizes in Systematic Reviews of Complex Interventions
... pooled. Distributions were plotted and fitted against the inverse power law (Pareto) and stretched exponential (Weibull) distributions, heavy tailed distributions which are commonly ...
7
A Robust Estimator of R = P(X > Y ) of Heavy tailed Distributions and its Sampling Distributions
... Heavy-tails are characteristics of many phenom- ena where the probability of a single huge value impacts heavily. Record-breaking insurance losses, financial log returns, file sizes stored on a server, transmission ...
5
Heavy-tailed distributions : data, diagnostics, and new developments
... thin-tailed distributions the estimator is biased, since the probability in question decreases to zero but the estimator is non-negative on initial ...
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A review of conditional rare event simulation for tail probabilities of heavy tailed random variables
... that distributions within the class S should be ap- propriate for modeling those phenomena which show some stability through time but eventually are shocked by an extreme ...Subexponential distributions ...
22
Pitfalls in using Weibull tailed distributions
... Statement 4: not enough for estimating an extreme tail probability. It is known that heavy tailed distributions can be employed to estimate both high quantiles and extreme tail probabilities. ...
12
Manpower Systems Operating under Heavy and Light Tailed Inter Exit Time Distributions
... All these results relating to E ( ) τ obtained above have been considered for a numerical study with specific in- put values “ν = 1.2, β = 0.75, α =1.2, λ = 2.0, and µ = 0.8” allowing n to vary from 1 to 10 and the ...
7
Singularity analysis for heavy tailed random variables
... for heavy-tailed distributions studied in this paper are of non-holonomic type and our methods of studying them show a new application of Lindel¨ of’s construction that has novel connections to other ...
41
Impact of Different Random Initializations on Generalization Performance of Extreme Learning Machine
... probability distributions on the training and testing accuracies of ...probability distributions [16] as shown in Table 1 are introduced in our study to initialize the input-layer weights and hidden-layer ...
18
Heavy-tailed distribution in the presence of dependence in insurance and finance
... the heavy-tailed distributions into the renewal risk model based on the two dependent assumptions, namely, dependence among claim sizes and de- pendence between claims and their ...
82
Heavy-tailed modeling of CROBEX
... More details on the method can be found in Grahovac et al. (2015). It is important to note that the estimation does not depend on the particular form of the underlying distribution and the only assumption is that the ...
20
The impact of heavy tails and comovements in downside-risk diversification
... towards heavy tailed distributions, see Fama (1965) or modern books on risk management and heavy tails as Embrechts (2000) or Malevergne and Sornette ...study heavy tails and extreme ...
27
Evaluation of a compound distribution based on weather pattern subsampling for extreme rainfall in Norway
... In Norway, a simple event-based rainfall–runoff model, PQRUT, has been used since the 1980s as a simulation method for dam safety analyses for which the magnitude of low frequency events (e.g., 500-, 1000-year peak ...
15
A New Method for Generalizing Burr and Related Distributions
... competitive distributions in almost all of the ...other heavy-tailed ...these heavy-tailed network data sets when modeled in the whole range using the proposed NBurr distribution shows ...
30
Asymptotics for risk capital allocations based on Conditional Tail Expectation
... all distributions with rapidly varying tails. Moderately heavy-tailed distributions such as lognormal and Weibull as well as light-tailed distributions such as exponential and ...
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