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Combinatorial aspects of a discrete parking process 离散停车过程的组合方面
IF 0.7 4区 数学 Q3 STATISTICS & PROBABILITY
Statistics & Probability Letters
Pub Date : 2026-06-01 Epub Date: 2026-02-12 DOI: 10.1016/j.spl.2026.110682
Robinson Higuita-Diaz , Lykos López , Alejandro Roldán-Correa
This article examines a discrete parking process on a line of n sites, where particles arrive sequentially, choosing a position uniformly at random among the currently available sites, and occupy a site only if it and its neighbors are vacant. The process ends when no further placements are possible, yielding a jamming limit configuration. We analyze combinatorial properties of the space of such configurations, including the enumeration of specific subsets. To contrast with the sequential dynamics, we introduce a static model in which all admissible jamming configurations are equally likely. For this model, we establish results on occupancy probabilities, the distribution and mean of occupied sites, and asymptotic occupancy density. A key finding is that the static model is stochastically dominated by the sequential one in terms of total occupancy. The study highlights structural and probabilistic differences between the models, contributing to the understanding of parking processes and random sequential adsorption.
本文研究了一条有n个站点的直线上的离散停车过程，其中粒子顺序到达，在当前可用的站点中随机均匀地选择一个位置，并且只有当该站点及其相邻站点空置时才占用该站点。当不可能进一步放置时，该过程结束，产生干扰限制配置。我们分析了这些构型空间的组合性质，包括特定子集的枚举。与顺序动力学相比，我们引入了一个静态模型，其中所有允许的干扰构型都是等可能的。对于该模型，我们建立了占用概率、占用场地的分布和平均值以及渐近占用密度的结果。一个关键的发现是，静态模型在总占用率方面随机地受到顺序模型的支配。该研究强调了模型之间的结构和概率差异，有助于理解停车过程和随机顺序吸附。
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引用次数: 0
Qualitative identification conditions for causal effects under bad controls in linear structural equation models 线性结构方程模型中不良控制下因果效应的定性识别条件
IF 0.7 4区 数学 Q3 STATISTICS & PROBABILITY
Statistics & Probability Letters
Pub Date : 2026-06-01 Epub Date: 2026-01-13 DOI: 10.1016/j.spl.2026.110642
Chie Taguchi , Manabu Kuroki
This paper considers a situation where the cause–effect relationships among random variables are represented by a linear structural equation model and the corresponding directed acyclic graph. When the causal effect is not quantitatively identifiable, we propose two novel qualitative identification conditions for causal effects under bad controls.
本文考虑了随机变量间的因果关系用线性结构方程模型和相应的有向无环图表示的情况。当因果效应不能定量识别时，我们提出了两个新的定性识别条件，用于不良控制下的因果效应。
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引用次数: 0
Optimal three-level blocked designs via general minimum lower-order confounding criterion 基于一般最小低阶混杂准则的最优三层阻塞设计
IF 0.7 4区 数学 Q3 STATISTICS & PROBABILITY
Statistics & Probability Letters
Pub Date : 2026-06-01 Epub Date: 2026-01-30 DOI: 10.1016/j.spl.2026.110665
Zhi Li , Dennis K.J. Lin , Zhiming Li
This paper introduces a blocked general minimum lower-order confounding (B-GMC) criterion and focuses on constructing optimal three-level blocked designs. We obtain some necessary conditions for constructing B-GMC designs. In addition, all 27-run and some 81-run B-GMC designs are tabulated.
本文介绍了一种阻塞一般最小低阶混杂准则，并着重于构造最优的三层阻塞设计。得到了构造B-GMC设计的一些必要条件。此外，所有27跑和一些81跑的B-GMC设计被制成表格。
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引用次数: 0
The Stieltjes transform order and related ratio order Stieltjes变换阶和相关的比值阶
IF 0.7 4区 数学 Q3 STATISTICS & PROBABILITY
Statistics & Probability Letters
Pub Date : 2026-06-01 Epub Date: 2026-02-02 DOI: 10.1016/j.spl.2026.110663
Abdulaziz Alenazi , Khaled Mehrez
In this paper, we introduce the Stieltjes transform order, defined via the composition of the Laplace transform of a random variable. First, we establish the monotonicity of the hazard rate associated with a transformed distribution of a random variable X. As a consequence, we derive a sharp lower bound for the Stieltjes transform of X in terms of its first two inverse moments. Secondly, we investigate the Stieltjes transform ratio order and provide its characterizations, both via properties of the hazard rate and through the monotonicity properties of higher-order Stieltjes transforms together with moment inequalities. We further establish explicit connections between the proposed orders and classical stochastic orders, including equivalence with the usual stochastic order and implication from the likelihood ratio order. These results enhance our understanding of stochastic orders and open new avenues for applications in reliability theory, economics, and applied probability.
本文引入了Stieltjes变换阶，它是由随机变量的拉普拉斯变换的复合定义的。首先，我们建立了与随机变量X的变换分布相关的风险率的单调性。因此，我们根据X的前两个逆矩导出了X的Stieltjes变换的明显下界。其次，通过危险率的性质和高阶Stieltjes变换与矩不等式的单调性性质，研究了Stieltjes变换比阶，并给出了其表征。我们进一步建立了所提阶与经典随机阶之间的明确联系，包括与通常随机阶的等价性和来自似然比阶的暗示。这些结果增强了我们对随机顺序的理解，并为可靠性理论、经济学和应用概率的应用开辟了新的途径。
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引用次数: 0
Transfer learning based on the single-index model 基于单指标模型的迁移学习
IF 0.7 4区 数学 Q3 STATISTICS & PROBABILITY
Statistics & Probability Letters
Pub Date : 2026-06-01 Epub Date: 2026-01-30 DOI: 10.1016/j.spl.2026.110667
Fengli Song, Yurong Zhang, Zhou Wang, Peng Lai
We introduce two transfer learning algorithms based on the single-index model, tailored for settings where the transferable data are either known or unknown. Theoretical properties of the proposed models are discussed. Their performance is evaluated through numerical simulations and applied to Genotype-Tissue Expression data.
我们介绍了两种基于单索引模型的迁移学习算法，为可转移数据已知或未知的设置量身定制。讨论了所提模型的理论性质。它们的性能通过数值模拟进行评估，并应用于基因型组织表达数据。
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引用次数: 0
The autocorrelation structure of integer-valued autoregressive random fields 整值自回归随机场的自相关结构
IF 0.7 4区 数学 Q3 STATISTICS & PROBABILITY
Statistics & Probability Letters
Pub Date : 2026-06-01 Epub Date: 2026-02-07 DOI: 10.1016/j.spl.2026.110681
Angelika Silbernagel, Christian H. Weiß
After clarifying possible misunderstandings concerning covariances of thinned random variables, we propose a refined definition of the first-order integer-valued autoregressive model for count random fields. We provide a comprehensive derivation of its autocorrelation structure, which also covers some former results. Moreover, we expand the refined model to higher-order autoregressions and study its stochastic properties.
在澄清了关于稀疏随机变量协方差的可能误解之后，我们提出了计数随机场的一阶整值自回归模型的改进定义。我们提供了一个全面的自相关结构的推导，也涵盖了一些以前的结果。此外，我们将改进后的模型扩展到高阶自回归，并研究了其随机性质。
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引用次数: 0
Total variation bounds in the Lindeberg central limit theorem 林德伯格中心极限定理中的总变分界
IF 0.7 4区 数学 Q3 STATISTICS & PROBABILITY
Statistics & Probability Letters
Pub Date : 2026-06-01 Epub Date: 2026-02-12 DOI: 10.1016/j.spl.2026.110687
Nguyen Tien Dung, Hoang Thi Phuong Thao
In this paper, we obtain an explicit total variation bound in the central limit theorem for the sums of independent random variables (not necessarily identically distributed). Our results show that, under suitable assumptions, Lindeberg’s condition is sufficient and necessary for the convergence in total variation distance.
本文给出了独立随机变量（不一定同分布）和的中心极限定理中一个显式的总变差界。结果表明，在适当的假设下，Lindeberg条件是总变差距离收敛的充分必要条件。
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引用次数: 0
Basis precision matrix estimation via column-wise inverse operator 基于列逆算子的基精度矩阵估计
IF 0.7 4区 数学 Q3 STATISTICS & PROBABILITY
Statistics & Probability Letters
Pub Date : 2026-06-01 Epub Date: 2026-02-10 DOI: 10.1016/j.spl.2026.110685
Shuwei Hu
This paper proposes an improved column-wise inverse operator method for precision matrix estimation of high-dimensional compositional data. We construct the estimator by using the truncated sample log-ratio covariance matrix and provide a probability bound on Gq(sn,p,Mn,p) under 4+ɛ (ɛ>0) moment condition. Simulations and a human gut microbiome dataset analysis confirm that the method works well.
提出了一种改进的列逆算子方法，用于高维成分数据的精确矩阵估计。利用截断样本对数比协方差矩阵构造了估计量，并给出了Gq（sn,p,Mn,p）在4+ ε (ε >0)矩条件下的概率界。模拟和人类肠道微生物组数据集分析证实了该方法的有效性。
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引用次数: 0
Group balancing generalized propensity score matching with continuous treatments 组平衡广义倾向评分与连续治疗匹配
IF 0.7 4区 数学 Q3 STATISTICS & PROBABILITY
Statistics & Probability Letters
Pub Date : 2026-06-01 Epub Date: 2026-02-02 DOI: 10.1016/j.spl.2026.110666
Kuan Sun, Zhiguo Xiao
We propose a new method for estimating the effect of a continuous treatment when data contains unobserved group-level differences. Our approach uses group-level averages of treatments and covariates as “group balancing statistics” to eliminate differences between groups. We introduce the Group Balancing Generalized Propensity Score Matching (GBGPSM) estimator, establish its asymptotic properties, and evaluate its performance through simulations.
当数据包含未观察到的组水平差异时，我们提出了一种新的方法来估计连续治疗的效果。我们的方法使用组水平的处理平均值和协变量作为“组平衡统计”来消除组之间的差异。引入了群体平衡广义倾向得分匹配（GBGPSM）估计器，建立了其渐近性质，并通过仿真对其性能进行了评价。
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引用次数: 0
Exponential stabilization via discrete-time feedback control for stochastic systems driven by G-Lévy process g - lsamvy过程驱动随机系统的离散时间反馈控制的指数镇定
IF 0.7 4区 数学 Q3 STATISTICS & PROBABILITY
Statistics & Probability Letters
Pub Date : 2026-05-01 Epub Date: 2026-01-08 DOI: 10.1016/j.spl.2026.110639
Bingjun Wang , Hongjun Gao , Mingxia Yuan
This paper investigates the exponential stabilization of stochastic systems driven by G-Lévy processes via discrete-time feedback control. We design a control input in the drift term based on discrete-time state observations and prove that there exists an upper bound τ̄>0 for the observation step size such that the controlled system achieves both mean square and quasi-sure exponential stability for any step size τ<τ̄. An illustrative example validates the effectiveness of the proposed control strategy.
本文通过离散时间反馈控制研究了由g - lsamvy过程驱动的随机系统的指数镇定问题。我们在漂移项中设计了一个基于离散时间状态观测的控制输入，并证明了观测步长存在一个上界τ τ >；0，使得被控系统在任意步长τ<；τ τ下均方稳定和准确定指数稳定。算例验证了所提控制策略的有效性。
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引用次数: 0
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