Results 11 to 20 of about 72,455 (264)
One-sided heavy tailed distributions have been used in many engineering applications, ranging from teletraffic modelling to financial engineering. In practice, the most interesting heavy tailed distributions are those having a finite mean and a diverging
Marco Cococcioni +2 more
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The Exponential T-X Family of Distributions: Properties and an Application to Insurance Data
Heavy-tailed distributions play a prominent role in actuarial and financial sciences. In this paper, we introduce a family of distributions that we refer to as exponential T-X (ETX) family.
Zubair Ahmad +4 more
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Hype and heavy tails: A closer look at data breaches [PDF]
Recent widely publicized data breaches have exposed thepersonal information of hundreds of millions of people. Somereports point to alarming increases in both the size and fre-quency of data breaches, spurring institutions around theworld to address what appears to be a worsening situation.But, is the problem actually growing worse?
Benjamin Edwards +2 more
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Asymptotic Expansions for Heavy-tailed Data
Heavy-tailed distributions are present in the characterization of different modern systems such as high-resolution imaging, cloud computing, and cognitive radio networks. Commonly, the cumulants of these distributions cannot be defined from a certain order, and this restricts the applicability of traditional methods.
Mora-Jimenez, Inmaculada +4 more
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On the Identification of the Riskiest Directional Components from Multivariate Heavy-Tailed Data
In univariate data, there exist standard procedures for identifying dominating features that produce the largest number of observations. However, in the multivariate setting, the situation is quite different.
Miriam Hägele, Jaakko Lehtomaa
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On Scheduling Policies With Heavy-Tailed Dynamics in Wireless Queueing Systems
This paper takes a system view and studies a wireless queueing system where heavy-tailness may occur both at the traffic arrival and in the form of the multi-user interference.
Shengbo Chen +5 more
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Background The distribution of residual effects in linear mixed models in animal breeding applications is typically assumed normal, which makes inferences vulnerable to outlier observations.
Garrick Dorian J +4 more
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Conditional mixture modelling for heavy‐tailed and skewed data
Overparameterization is a serious concern for multivariate mixture models as it can lead to model overfitting and, as a result, mixture order underestimation. Parsimonious modelling is one of the most effective remedies in this context. In Gaussian mixture models, the majority of parameters is associated with covariance matrices and parsimonious models
Dong, Aqi +3 more
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Type-I heavy tailed family with applications in medicine, engineering and insurance.
In the present study, a new class of heavy tailed distributions using the T-X family approach is introduced. The proposed family is called type-I heavy tailed family. A special model of the proposed class, named Type-I Heavy Tailed Weibull (TI-HTW) model
Wei Zhao +4 more
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Gini covariance plays a vital role in analyzing the relationship between random variables with heavy-tailed distributions. In this papaer, with the existence of a finite second moment, we establish the Gini–Yule–Walker equation to estimate the transition
Jin Zou, Dong Han
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