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Non-hyperuniformity of Gibbs point processes with short-range interactions 具有短程相互作用的吉布斯点过程的非超均匀性
IF 1 4区 数学 Q3 STATISTICS & PROBABILITY Pub Date : 2024-08-02 DOI: 10.1017/jpr.2024.21
David Dereudre, Daniela Flimmel
We investigate the hyperuniformity of marked Gibbs point processes that have weak dependencies among distant points whilst the interactions of close points are kept arbitrary. Various stability and range assumptions are imposed on the Papangelou intensity in order to prove that the resulting point process is not hyperuniform. The scope of our results covers many frequently used models, including Gibbs point processes with a superstable, lower-regular, integrable pair potential, as well as the Widom–Rowlinson model with random radii and Gibbs point processes with interactions based on Voronoi tessellations and nearest-neighbour graphs.
我们研究了标记吉布斯点过程的超均匀性,这种过程在远点之间具有弱依赖性,而近点之间的相互作用保持任意。为了证明所得到的点过程不是超均匀的,我们对帕潘吉洛强度施加了各种稳定性和范围假设。我们的结果涵盖了许多常用模型,包括具有超稳定、低规则、可整对势的吉布斯点过程,以及具有随机半径的 Widom-Rowlinson 模型和具有基于 Voronoi 网格和近邻图的相互作用的吉布斯点过程。
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引用次数: 0
On the speed of convergence of discrete Pickands constants to continuous ones 论离散皮康兹常数向连续常数的收敛速度
IF 1 4区 数学 Q3 STATISTICS & PROBABILITY Pub Date : 2024-07-31 DOI: 10.1017/jpr.2024.37
Krzysztof Bisewski, Grigori Jasnovidov
In this manuscript, we address open questions raised by Dieker and Yakir (2014), who proposed a novel method of estimating (discrete) Pickands constants <jats:inline-formula> <jats:alternatives> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" mime-subtype="png" xlink:href="S0021900224000378_inline1.png"/> <jats:tex-math> $mathcal{H}^delta_alpha$ </jats:tex-math> </jats:alternatives> </jats:inline-formula> using a family of estimators <jats:inline-formula> <jats:alternatives> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" mime-subtype="png" xlink:href="S0021900224000378_inline2.png"/> <jats:tex-math> $xi^delta_alpha(T)$ </jats:tex-math> </jats:alternatives> </jats:inline-formula>, <jats:inline-formula> <jats:alternatives> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" mime-subtype="png" xlink:href="S0021900224000378_inline3.png"/> <jats:tex-math> $T>0$ </jats:tex-math> </jats:alternatives> </jats:inline-formula>, where <jats:inline-formula> <jats:alternatives> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" mime-subtype="png" xlink:href="S0021900224000378_inline4.png"/> <jats:tex-math> $alphain(0,2]$ </jats:tex-math> </jats:alternatives> </jats:inline-formula> is the Hurst parameter, and <jats:inline-formula> <jats:alternatives> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" mime-subtype="png" xlink:href="S0021900224000378_inline5.png"/> <jats:tex-math> $deltageq0$ </jats:tex-math> </jats:alternatives> </jats:inline-formula> is the step size of the regular discretization grid. We derive an upper bound for the discretization error <jats:inline-formula> <jats:alternatives> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" mime-subtype="png" xlink:href="S0021900224000378_inline6.png"/> <jats:tex-math> $mathcal{H}_alpha^0 - mathcal{H}_alpha^delta$ </jats:tex-math> </jats:alternatives> </jats:inline-formula>, whose rate of convergence agrees with Conjecture 1 of Dieker and Yakir (2014) in the case <jats:inline-formula> <jats:alternatives> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" mime-subtype="png" xlink:href="S0021900224000378_inline7.png"/> <jats:tex-math> $alphain(0,1]$ </jats:tex-math> </jats:alternatives> </jats:inline-formula> and agrees up to logarithmic terms for <jats:inline-formula> <jats:alternatives> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" mime-subtype="png" xlink:href="S0021900224000378_inline8.png"/> <jats:tex-math> $alphain(1,2)$ </jats:tex-math> </jats:alternatives> </jats:inline-formula>. Moreover, we show that all moments of <jats:inline-formula> <jats:alternatives> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" mime-subtype="png" xlink:href="S0021900224000378_inline9.png"/> <jats:tex-math> $xi_alpha^delta(T)$ </jats:tex-math> </jats:alternatives> </jats:inline-formula> are uniformly bounded and the bias of the estimator decays no slower than <jats:inline-formula> <jats:alte
在本手稿中,我们将讨论 Dieker 和 Yakir(2014 年)提出的开放性问题,他们提出了一种新方法,即使用估计器系列 $xi^delta_alpha(T)$ , $T>0$ 来估计(离散)皮克兰常数 $mathcal{H}^delta_alpha$ ,其中 $alphain(0,2]$ 是赫斯特参数,$deltageq0$ 是常规离散网格的步长。我们推导出离散化误差 $mathcal{H}_alpha^0 - mathcal{H}_alpha^delta$的上界,其收敛率在$alpha/in(0,1]$情况下与Dieker和Yakir(2014)的猜想1一致,在$alpha/in(1,2)$情况下与对数项一致。此外,我们还证明了$xi_alpha^delta(T)$的所有矩都是均匀有界的,并且当T变大时,估计器偏差的衰减速度不会慢于$exp{-mathcal CT^{alpha}}$ 。
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引用次数: 0
Persistence of spectral projections for stochastic operators on large tensor products 大张量乘上随机算子谱投影的持久性
IF 1 4区 数学 Q3 STATISTICS & PROBABILITY Pub Date : 2024-06-03 DOI: 10.1017/jpr.2024.34
Robert S. Mackay

It is proved that for families of stochastic operators on a countable tensor product, depending smoothly on parameters, any spectral projection persists smoothly, where smoothness is defined using norms based on ideas of Dobrushin. A rigorous perturbation theory for families of stochastic operators with spectral gap is thereby created. It is illustrated by deriving an effective slow two-state dynamics for a three-state probabilistic cellular automaton.

研究证明,对于可数张量积上的随机算子族,在平稳地依赖于参数的情况下,任何谱投影都会平稳地持续存在,其中平稳性是使用基于多布鲁欣思想的规范来定义的。由此,我们创建了具有谱间隙的随机算子族的严格扰动理论。我们通过推导三态概率蜂窝自动机的有效慢速双态动力学来说明这一点。
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引用次数: 0
Bivariate tempered space-fractional Poisson process and shock models 双变量节制空间分数泊松过程和冲击模型
IF 1 4区 数学 Q3 STATISTICS & PROBABILITY Pub Date : 2024-05-23 DOI: 10.1017/jpr.2024.30
Ritik Soni, Ashok Kumar Pathak, Antonio Di Crescenzo, Alessandra Meoli
We introduce a bivariate tempered space-fractional Poisson process (BTSFPP) by time-changing the bivariate Poisson process with an independent tempered $alpha$ -stable subordinator. We study its distributional properties and its connection to differential equations. The Lévy measure for the BTSFPP is also derived. A bivariate competing risks and shock model based on the BTSFPP for predicting the failure times of items that undergo two random shocks is also explored. The system is supposed to break when the sum of two types of shock reaches a certain random threshold. Various results related to reliability, such as reliability function, hazard rates, failure density, and the probability that failure occurs due to a certain type of shock, are studied. We show that for a general Lévy subordinator, the failure time of the system is exponentially distributed with mean depending on the Laplace exponent of the Lévy subordinator when the threshold has a geometric distribution. Some special cases and several typical examples are also demonstrated.
我们引入了双变量有节制空间分数泊松过程(BTSFPP),即用独立的有节制 $alpha$ - 稳定从量对双变量泊松过程进行时变。我们研究了它的分布特性及其与微分方程的联系。我们还推导出了 BTSFPP 的 Lévy 度量。我们还探讨了一个基于 BTSFPP 的双变量竞争风险和冲击模型,用于预测经历两次随机冲击的物品的失效时间。当两种冲击的总和达到某个随机阈值时,系统就会崩溃。我们研究了与可靠性有关的各种结果,如可靠性函数、危险率、失效密度和因某类冲击而发生失效的概率。我们证明,对于一般的莱维从属器,当阈值具有几何分布时,系统的失效时间呈指数分布,其均值取决于莱维从属器的拉普拉斯指数。我们还展示了一些特例和几个典型例子。
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引用次数: 0
Geometric random intersection graphs with general connection probabilities 具有一般连接概率的几何随机相交图
IF 1 4区 数学 Q3 STATISTICS & PROBABILITY Pub Date : 2024-05-22 DOI: 10.1017/jpr.2024.18
Maria Deijfen, Riccardo Michielan
Let <jats:inline-formula> <jats:alternatives> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" mime-subtype="png" xlink:href="S0021900224000184_inline1.png"/> <jats:tex-math> $mathcal{V}$ </jats:tex-math> </jats:alternatives> </jats:inline-formula> and <jats:inline-formula> <jats:alternatives> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" mime-subtype="png" xlink:href="S0021900224000184_inline2.png"/> <jats:tex-math> $mathcal{U}$ </jats:tex-math> </jats:alternatives> </jats:inline-formula> be the point sets of two independent homogeneous Poisson processes on <jats:inline-formula> <jats:alternatives> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" mime-subtype="png" xlink:href="S0021900224000184_inline3.png"/> <jats:tex-math> $mathbb{R}^d$ </jats:tex-math> </jats:alternatives> </jats:inline-formula>. A graph <jats:inline-formula> <jats:alternatives> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" mime-subtype="png" xlink:href="S0021900224000184_inline4.png"/> <jats:tex-math> $mathcal{G}_mathcal{V}$ </jats:tex-math> </jats:alternatives> </jats:inline-formula> with vertex set <jats:inline-formula> <jats:alternatives> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" mime-subtype="png" xlink:href="S0021900224000184_inline5.png"/> <jats:tex-math> $mathcal{V}$ </jats:tex-math> </jats:alternatives> </jats:inline-formula> is constructed by first connecting pairs of points (<jats:italic>v</jats:italic>, <jats:italic>u</jats:italic>) with <jats:inline-formula> <jats:alternatives> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" mime-subtype="png" xlink:href="S0021900224000184_inline6.png"/> <jats:tex-math> $vinmathcal{V}$ </jats:tex-math> </jats:alternatives> </jats:inline-formula> and <jats:inline-formula> <jats:alternatives> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" mime-subtype="png" xlink:href="S0021900224000184_inline7.png"/> <jats:tex-math> $uinmathcal{U}$ </jats:tex-math> </jats:alternatives> </jats:inline-formula> independently with probability <jats:inline-formula> <jats:alternatives> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" mime-subtype="png" xlink:href="S0021900224000184_inline8.png"/> <jats:tex-math> $g(v-u)$ </jats:tex-math> </jats:alternatives> </jats:inline-formula>, where <jats:italic>g</jats:italic> is a non-increasing radial function, and then connecting two points <jats:inline-formula> <jats:alternatives> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" mime-subtype="png" xlink:href="S0021900224000184_inline9.png"/> <jats:tex-math> $v_1,v_2inmathcal{V}$ </jats:tex-math> </jats:alternatives> </jats:inline-formula> if and only if they have a joint neighbor <jats:inline-formula> <jats:alternatives> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" mime-subtype="png" xlink:href="S0021900224000184_inline10.png"/> <jats:tex-math> $uinmathcal{U}$ </jats:tex-math> </jats:alternati
让 $mathcal{V}$ 和 $mathcal{U}$ 是 $mathbb{R}^d$ 上两个独立同质泊松过程的点集。首先以 $g(v-u)$ 的概率将 $vinmathcal{V}$ 和 $uinmathcal{U}$ 独立的点对 (v, u) 连接起来,就构建了一个顶点集为 $mathcal{V}$ 的图 $mathcal{G}_mathcal{V}$ 、其中 g 是一个非递增的径向函数,然后连接两个点 $v_1,v_2inmathcal{V}$ 当且仅当它们有一个共同的邻居 $uinmathcal{U}$ 。这就产生了 $mathbb{R}^d$ 上的随机交集图。此外,该图的渗流特性根据 g 的有界或无界支持而有所不同。
{"title":"Geometric random intersection graphs with general connection probabilities","authors":"Maria Deijfen, Riccardo Michielan","doi":"10.1017/jpr.2024.18","DOIUrl":"https://doi.org/10.1017/jpr.2024.18","url":null,"abstract":"Let &lt;jats:inline-formula&gt; &lt;jats:alternatives&gt; &lt;jats:inline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" mime-subtype=\"png\" xlink:href=\"S0021900224000184_inline1.png\"/&gt; &lt;jats:tex-math&gt; $mathcal{V}$ &lt;/jats:tex-math&gt; &lt;/jats:alternatives&gt; &lt;/jats:inline-formula&gt; and &lt;jats:inline-formula&gt; &lt;jats:alternatives&gt; &lt;jats:inline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" mime-subtype=\"png\" xlink:href=\"S0021900224000184_inline2.png\"/&gt; &lt;jats:tex-math&gt; $mathcal{U}$ &lt;/jats:tex-math&gt; &lt;/jats:alternatives&gt; &lt;/jats:inline-formula&gt; be the point sets of two independent homogeneous Poisson processes on &lt;jats:inline-formula&gt; &lt;jats:alternatives&gt; &lt;jats:inline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" mime-subtype=\"png\" xlink:href=\"S0021900224000184_inline3.png\"/&gt; &lt;jats:tex-math&gt; $mathbb{R}^d$ &lt;/jats:tex-math&gt; &lt;/jats:alternatives&gt; &lt;/jats:inline-formula&gt;. A graph &lt;jats:inline-formula&gt; &lt;jats:alternatives&gt; &lt;jats:inline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" mime-subtype=\"png\" xlink:href=\"S0021900224000184_inline4.png\"/&gt; &lt;jats:tex-math&gt; $mathcal{G}_mathcal{V}$ &lt;/jats:tex-math&gt; &lt;/jats:alternatives&gt; &lt;/jats:inline-formula&gt; with vertex set &lt;jats:inline-formula&gt; &lt;jats:alternatives&gt; &lt;jats:inline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" mime-subtype=\"png\" xlink:href=\"S0021900224000184_inline5.png\"/&gt; &lt;jats:tex-math&gt; $mathcal{V}$ &lt;/jats:tex-math&gt; &lt;/jats:alternatives&gt; &lt;/jats:inline-formula&gt; is constructed by first connecting pairs of points (&lt;jats:italic&gt;v&lt;/jats:italic&gt;, &lt;jats:italic&gt;u&lt;/jats:italic&gt;) with &lt;jats:inline-formula&gt; &lt;jats:alternatives&gt; &lt;jats:inline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" mime-subtype=\"png\" xlink:href=\"S0021900224000184_inline6.png\"/&gt; &lt;jats:tex-math&gt; $vinmathcal{V}$ &lt;/jats:tex-math&gt; &lt;/jats:alternatives&gt; &lt;/jats:inline-formula&gt; and &lt;jats:inline-formula&gt; &lt;jats:alternatives&gt; &lt;jats:inline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" mime-subtype=\"png\" xlink:href=\"S0021900224000184_inline7.png\"/&gt; &lt;jats:tex-math&gt; $uinmathcal{U}$ &lt;/jats:tex-math&gt; &lt;/jats:alternatives&gt; &lt;/jats:inline-formula&gt; independently with probability &lt;jats:inline-formula&gt; &lt;jats:alternatives&gt; &lt;jats:inline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" mime-subtype=\"png\" xlink:href=\"S0021900224000184_inline8.png\"/&gt; &lt;jats:tex-math&gt; $g(v-u)$ &lt;/jats:tex-math&gt; &lt;/jats:alternatives&gt; &lt;/jats:inline-formula&gt;, where &lt;jats:italic&gt;g&lt;/jats:italic&gt; is a non-increasing radial function, and then connecting two points &lt;jats:inline-formula&gt; &lt;jats:alternatives&gt; &lt;jats:inline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" mime-subtype=\"png\" xlink:href=\"S0021900224000184_inline9.png\"/&gt; &lt;jats:tex-math&gt; $v_1,v_2inmathcal{V}$ &lt;/jats:tex-math&gt; &lt;/jats:alternatives&gt; &lt;/jats:inline-formula&gt; if and only if they have a joint neighbor &lt;jats:inline-formula&gt; &lt;jats:alternatives&gt; &lt;jats:inline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" mime-subtype=\"png\" xlink:href=\"S0021900224000184_inline10.png\"/&gt; &lt;jats:tex-math&gt; $uinmathcal{U}$ &lt;/jats:tex-math&gt; &lt;/jats:alternati","PeriodicalId":50256,"journal":{"name":"Journal of Applied Probability","volume":"54 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141152704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Depths in random recursive metric spaces 随机递归度量空间中的深度
IF 1 4区 数学 Q3 STATISTICS & PROBABILITY Pub Date : 2024-05-20 DOI: 10.1017/jpr.2024.32
Colin Desmarais
As a generalization of random recursive trees and preferential attachment trees, we consider random recursive metric spaces. These spaces are constructed from random blocks, each a metric space equipped with a probability measure, containing a labelled point called a hook, and assigned a weight. Random recursive metric spaces are equipped with a probability measure made up of a weighted sum of the probability measures assigned to its constituent blocks. At each step in the growth of a random recursive metric space, a point called a latch is chosen at random according to the equipped probability measure, and a new block is chosen at random and attached to the space by joining together the latch and the hook of the block. We use martingale theory to prove a law of large numbers and a central limit theorem for the insertion depth, the distance from the master hook to the latch chosen. We also apply our results to further generalizations of random trees, hooking networks, and continuous spaces constructed from line segments.
作为随机递归树和优先附着树的一般化,我们考虑随机递归度量空间。这些空间由随机块构建而成,每个块都是一个配备概率度量的度量空间,包含一个称为钩子的标记点,并被赋予一个权重。随机递归度量空间的概率度量由分配给其组成块的概率度量的加权和组成。在随机递归度量空间的每一步增长中,都会根据所配备的概率度量随机选择一个称为 "闩 "的点,并随机选择一个新的块,通过将 "闩 "和块的 "钩 "连接在一起,将其附加到空间中。我们利用鞅理论证明了插入深度的大数定律和中心极限定理,即从主钩到所选锁存点的距离。我们还将结果应用于随机树、挂钩网络和由线段构造的连续空间的进一步推广。
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引用次数: 0
Multivariate regularly varying insurance and financial risks in multidimensional risk models 多维风险模型中的多变量有规律变化的保险和金融风险
IF 1 4区 数学 Q3 STATISTICS & PROBABILITY Pub Date : 2024-05-13 DOI: 10.1017/jpr.2024.23
Ming Cheng, Dimitrios G. Konstantinides, Dingcheng Wang
Multivariate regular variation is a key concept that has been applied in finance, insurance, and risk management. This paper proposes a new dependence assumption via a framework of multivariate regular variation. Under the condition that financial and insurance risks satisfy our assumption, we conduct asymptotic analyses for multidimensional ruin probabilities in the discrete-time and continuous-time cases. Also, we present a two-dimensional numerical example satisfying our assumption, through which we show the accuracy of the asymptotic result for the discrete-time multidimensional insurance risk model.
多变量正则变异是一个关键概念,已被应用于金融、保险和风险管理领域。本文通过多变量正则变异框架提出了一种新的依赖性假设。在金融和保险风险满足假设的条件下,我们对离散时间和连续时间情况下的多维毁坏概率进行了渐近分析。此外,我们还给出了一个满足我们假设的二维数值示例,通过该示例,我们展示了离散时间多维保险风险模型渐近结果的准确性。
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引用次数: 0
Perturbation analysis for continuous-time Markov chains in a weak sense 弱意义上连续时间马尔可夫链的扰动分析
IF 1 4区 数学 Q3 STATISTICS & PROBABILITY Pub Date : 2024-05-13 DOI: 10.1017/jpr.2024.20
Na Lin, Yuanyuan Liu
By the technique of augmented truncations, we obtain the perturbation bounds on the distance of the finite-time state distributions of two continuous-time Markov chains (CTMCs) in a type of weaker norm than the V-norm. We derive the estimates for strongly and exponentially ergodic CTMCs. In particular, we apply these results to get the bounds for CTMCs satisfying Doeblin or stochastically monotone conditions. Some examples are presented to illustrate the limitation of the V-norm in perturbation analysis and to show the quality of the weak norm.
通过增强截断技术,我们得到了两个连续时间马尔可夫链(CTMC)的有限时间状态分布距离的扰动边界,其规范类型比 V 规范更弱。我们推导了强遍历和指数遍历 CTMC 的估计值。特别是,我们应用这些结果得到了满足多布林或随机单调条件的 CTMC 的边界。我们列举了一些例子来说明 V 准则在扰动分析中的局限性,并展示了弱准则的质量。
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引用次数: 0
Branching processes in nearly degenerate varying environment 近乎退化的变化环境中的分支过程
IF 1 4区 数学 Q3 STATISTICS & PROBABILITY Pub Date : 2024-05-10 DOI: 10.1017/jpr.2024.15
Péter Kevei, Kata Kubatovics
We investigate branching processes in varying environment, for which $overline{f}_n to 1$ and $sum_{n=1}^infty (1-overline{f}_n)_+ = infty$ , $sum_{n=1}^infty (overline{f}_n - 1)_+ < infty$ , where $overline{f}_n$ stands for the offspring mean in generation n. Since subcritical regimes dominate, such processes die out almost surely, therefore to obtain a nontrivial limit we consider two scenarios: conditioning on nonextinction, and adding immigration. In both cases we show that the process converges in distribution without normalization to a nondegenerate compound-Poisson limit law. The proofs rely on the shape function technique, worked out by Kersting (2020).
我们研究了变化环境中的分支过程,对于这种过程,$overline{f}_n to 1$,$sum_{n=1}^infty (1-overline{f}_n)_+ = infty$,$sum_{n=1}^infty (overline{f}_n - 1)_+ < infty$,其中$overline{f}_n$代表第 n 代的后代平均值。由于亚临界状态占主导地位,这种过程几乎肯定会消亡,因此,为了得到一个非微观极限,我们考虑了两种情况:以不消亡为条件,以及增加移民。在这两种情况下,我们都证明了该过程在分布上无需归一化即可收敛到非退化的复合泊松极限规律。证明依赖于 Kersting(2020 年)提出的形状函数技术。
{"title":"Branching processes in nearly degenerate varying environment","authors":"Péter Kevei, Kata Kubatovics","doi":"10.1017/jpr.2024.15","DOIUrl":"https://doi.org/10.1017/jpr.2024.15","url":null,"abstract":"We investigate branching processes in varying environment, for which <jats:inline-formula> <jats:alternatives> <jats:inline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" mime-subtype=\"png\" xlink:href=\"S0021900224000159_inline1.png\"/> <jats:tex-math> $overline{f}_n to 1$ </jats:tex-math> </jats:alternatives> </jats:inline-formula> and <jats:inline-formula> <jats:alternatives> <jats:inline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" mime-subtype=\"png\" xlink:href=\"S0021900224000159_inline2.png\"/> <jats:tex-math> $sum_{n=1}^infty (1-overline{f}_n)_+ = infty$ </jats:tex-math> </jats:alternatives> </jats:inline-formula>, <jats:inline-formula> <jats:alternatives> <jats:inline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" mime-subtype=\"png\" xlink:href=\"S0021900224000159_inline3.png\"/> <jats:tex-math> $sum_{n=1}^infty (overline{f}_n - 1)_+ &lt; infty$ </jats:tex-math> </jats:alternatives> </jats:inline-formula>, where <jats:inline-formula> <jats:alternatives> <jats:inline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" mime-subtype=\"png\" xlink:href=\"S0021900224000159_inline4.png\"/> <jats:tex-math> $overline{f}_n$ </jats:tex-math> </jats:alternatives> </jats:inline-formula> stands for the offspring mean in generation <jats:italic>n</jats:italic>. Since subcritical regimes dominate, such processes die out almost surely, therefore to obtain a nontrivial limit we consider two scenarios: conditioning on nonextinction, and adding immigration. In both cases we show that the process converges in distribution without normalization to a nondegenerate compound-Poisson limit law. The proofs rely on the shape function technique, worked out by Kersting (2020).","PeriodicalId":50256,"journal":{"name":"Journal of Applied Probability","volume":"15 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140930070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A remark on exact simulation of tempered stable Ornstein–Uhlenbeck processes 关于回火稳定奥恩斯坦-乌伦贝克过程精确模拟的评论
IF 1 4区 数学 Q3 STATISTICS & PROBABILITY Pub Date : 2024-05-02 DOI: 10.1017/jpr.2024.17
Takuji Arai, Yuto Imai
Qu, Dassios, and Zhao (2021) suggested an exact simulation method for tempered stable Ornstein–Uhlenbeck processes, but their algorithms contain some errors. This short note aims to correct their algorithms and conduct some numerical experiments.
Qu、Dassios 和 Zhao(2021 年)提出了回火稳定奥恩斯坦-乌伦贝克过程的精确模拟方法,但他们的算法包含一些错误。这篇短文旨在纠正他们的算法,并进行一些数值实验。
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引用次数: 0
期刊
Journal of Applied Probability
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