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相关论文: Extremal properties of the univariate extended ske…

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The skew-normal and related families are flexible and asymmetric parametric models suitable for modelling a diverse range of systems. We show that the multivariate maximum of a high-dimensional extended skew-normal random sample has…

统计方法学 · 统计学 2018-10-02 Boris Beranger , Simone A. Padoan , Yangfan Xu , Scott A. Sisson

In this paper, we study the asymptotic behaviors of the extreme of mixed skew-t distribution. We considered limits on distribution and density of maximum of mixed skew-t distribution under linear and power normalization, and further derived…

统计理论 · 数学 2016-06-13 Jingyao Hou , Xin Liao , Zuoxiang Peng

For a skew normal random sequence, convergence rates of the distribution of its partial maximum to the Gumbel extreme value distribution are derived. The asymptotic expansion of the distribution of the normalized maximum is given under an…

统计方法学 · 统计学 2012-12-06 Xin Liao , Zuoxiang Peng , Saralees Nadarajah , Xiaoqian Wang

Let $M_n=\max \left(X_1, X_2, \ldots, X_n \right)$ denote the partial maximum of an independent and identically distributed skew-normal random sequence. In this paper, the rate of uniform convergence of skew-normal extremes is derived. It…

概率论 · 数学 2023-02-20 Qian Xiong , Zuoxiang Peng , Saralees Nadarajah

Max-stable distributions and processes are important models for extreme events and the assessment of tail risks. The full, multivariate likelihood of a parametric max-stable distribution is complicated and only recent advances enable its…

统计理论 · 数学 2017-08-08 Clement Dombry , Sebastian Engelke , Marco Oesting

The family of multivariate skew-normal distributions has many interesting properties. It is shown here that these hold for a general class of skew-elliptical distributions. For this class, several stochastic representations are established…

统计理论 · 数学 2023-09-18 Chuancun Yin , Narayanaswamy Balakrishnan

The classical multivariate extreme-value theory concerns the modeling of extremes in a multivariate random sample, suggesting the use of max-stable distributions. In this work, the classical theory is extended to the case where aggregated…

统计方法学 · 统计学 2020-03-12 Enkelejd Hashorva , Simone A. Padoan , Stefano Rizzelli

We study extremal statistics and return intervals in stationary long-range correlated sequences for which the underlying probability density function is bounded and uniform. The extremal statistics we consider e.g., maximum relative to…

统计力学 · 物理学 2015-05-13 N. R. Moloney , J. Davidsen

In this paper we propose a family of multivariate asymmetric distributions over an arbitrary subset of set of real numbers which is defined in terms of the well-known elliptically symmetric distributions. We explore essential properties,…

统计方法学 · 统计学 2024-09-02 Roberto Vila , Helton Saulo , Leonardo Santos , João Monteiros , Felipe Quintino

For the family of multivariate probability distributions variously denoted as unified skew-normal, closed skew-normal and other names, a number of properties are already known, but many others are not, even some basic ones. The present…

统计理论 · 数学 2020-11-13 Reinaldo B. Arellano-Valle , Adelchi Azzalini

Generalized Maxwell distribution is an extension of the classic Maxwell distribution. In this paper, we concentrate on the joint distributional asymptotics of normalized maxima and minima. Under optimal normalizing constants, asymptotic…

概率论 · 数学 2020-03-10 Jianwen Huang

In this work, we derive some novel properties of the bimodal normal distribution. Some of its mathematical properties are examined. We provide a formal proof for the bimodality and assess identifiability. We then discuss the maximum…

统计理论 · 数学 2021-06-02 Roberto Vila , Helton Saulo , Jamer Roldan

For the extended skew-normal distribution, which represents an extension of the normal (or Gaussian) distribution, we focus on the properties of the log-likelihood function and derived quantities in the the bivariate case. Specifically, we…

统计理论 · 数学 2023-09-20 Stefano Franco , Adelchi Azzalini

Azzalini & Dalla Valle (1996) have recently discussed the multivariate skew-normal distribution which extends the class of normal distributions by the addition of a shape parameter. The first part of the present paper examines further…

统计方法学 · 统计学 2009-11-12 Adelchi Azzalini , Antonella Capitanio

The statistical distribution of the ratio of two normal random variables is characterized by its heavy-tailed nature and absence of finite moments. The shape of its density function is highly variable, capable of exhibiting unimodal or…

概率论 · 数学 2023-11-07 Sheng Yang , Zhengtao Gui

Multivariate extreme value distributions are a common choice for modelling multivariate extremes. In high dimensions, however, the construction of flexible and parsimonious models is challenging. We propose to combine bivariate max-stable…

统计方法学 · 统计学 2024-12-25 Shuang Hu , Zuoxiang Peng , Johan Segers

The multivariate extended skew-normal distribution allows for accommodating raw data which are skewed and heavy tailed, and has at least three appealing statistical properties, namely closure under conditioning, affine transformations, and…

统计方法学 · 统计学 2015-06-19 Mathieu Gerber , Florian Pelgrin

In this note, we obtain verifiable sufficient conditions for the extreme value distribution for a certain class of skew product extensions of non-uniformly hyperbolic base maps. We show that these conditions, formulated in terms of the…

动力系统 · 数学 2008-10-27 Chinmaya Gupta

Skew-symmetric families of distributions such as the skew-normal and skew-$t$ represent supersets of the normal and $t$ distributions, and they exhibit richer classes of extremal behaviour. By defining a non-stationary skew-normal process,…

统计方法学 · 统计学 2016-04-19 Boris Beranger , Simone A. Padoan , Scott A. Sisson

In this paper, asymptotic expansions of the distributions and densities of powered extremes for Maxwell samples are considered. The results show that the convergence speeds of normalized partial maxima relies on the powered index.…

概率论 · 数学 2020-03-10 Jianwen Huang , Xinling Liu , Jianjun Wang , Zhongquan Tan , Jingyao Hou , Hao Pu
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