Article
Computer Science, Interdisciplinary Applications
Jiayi Deng, Danyang Huang, Yi Ding, Yingqiu Zhu, Bingyi Jing, Bo Zhang
Summary: This study proposes a subsampling spectral clustering algorithm to address the computational challenges of large-scale network data. By constructing a subnetwork through simple random subsampling and extending the spectral clustering method, the algorithm can identify community structures in the entire network with limited computing resources. The method also has the potential for parallelization and theoretical properties are established under the stochastic block model.
COMPUTATIONAL STATISTICS & DATA ANALYSIS
(2024)
Article
Engineering, Mechanical
Axay Thapa, Atin Roy, Subrata Chakraborty
Summary: This article compares different metamodeling approaches for reliability analysis of tunnels to evaluate their performance. The study found that Kriging and support vector regression models perform well in estimating the reliability of underground tunnels.
PROBABILISTIC ENGINEERING MECHANICS
(2024)
Article
Statistics & Probability
Huiping Chen, Yong Chen, Yong Liu
Summary: This paper characterizes the relation between the real and complex Wiener-Ito integrals, providing explicit expressions for the kernels of their real and imaginary parts, and obtaining a representation formula for a two-dimensional real Wiener-Ito integral through a finite sum of complex Wiener-Ito integrals. The main tools used are a recursion technique and Malliavin derivative operators. As an application, the regularity of the stationary solution of the stochastic heat equation with dispersion is investigated.
STOCHASTIC PROCESSES AND THEIR APPLICATIONS
(2024)
Article
Engineering, Mechanical
Yufan Cheng, Xinchen Zhuang, Tianxiang Yu
Summary: This paper proposes a time-dependent kinematic reliability analysis method that takes into account the truncated random variables and joint clearances, effectively addressing the issues of dimension variables and correlation between joint clearance variables. The proposed method transforms time-dependent reliability into time-independent reliability, greatly reducing computational complexity and obtaining upper and lower bounds of failure probability.
PROBABILISTIC ENGINEERING MECHANICS
(2024)
Article
Economics
Sascha Gunther, Peter Hieber
Summary: The financial return of equity-indexed annuities depends on an underlying fund or investment portfolio complemented by an investment guarantee. This study introduces a novel scenario-matrix method for valuation and risk management, specifically for the cliquet-style or ratchet-type guarantee. Numerical tests show that this method outperforms existing approaches in terms of computation time and accuracy.
INSURANCE MATHEMATICS & ECONOMICS
(2024)
Article
Economics
Bingjie Wang, Jinzhu Li
Summary: This paper focuses on the asymptotic behavior of a popular risk measure called the tail moment (TM). The study reveals precise asymptotic results for the TM under scenarios where individual risks are mutually independent or have a specific dependence structure. Furthermore, the article provides an analysis of the relative errors between the asymptotic results and the exact values.
INSURANCE MATHEMATICS & ECONOMICS
(2024)
Article
Statistics & Probability
Amites Dasgupta
Summary: We present Azuma-Hoeffding bounds for a class of urn models, which show exponentially decreasing probabilities of being away from the limit. The method involves relating the variables to linear combinations using eigenvectors of the replacement matrix, and introduces appropriate martingales. Some cases of repeated eigenvalues are also considered using cyclic vectors. Moreover, the strong convergence of proportions is proved as an application of these bounds.
STATISTICS & PROBABILITY LETTERS
(2024)
Article
Computer Science, Interdisciplinary Applications
Cuihong Zhang, Jing Ning, Jianwen Cai, James E. Squires, Steven H. Belle, Ruosha Li
Summary: Modeling disease risk and survival using longitudinal risk factor trajectories can provide personalized information for clinical decision making. This study proposes a dynamic risk score modeling framework that can accommodate multiple longitudinal risk factors and dependent censoring, and generate parsimonious longitudinal risk scores. The proposed method demonstrates satisfactory performance in simulation studies and real-world application.
COMPUTATIONAL STATISTICS & DATA ANALYSIS
(2024)
Article
Statistics & Probability
Masafumi Hayashi, Atsushi Takeuchi, Makoto Yamazato
Summary: This article considers subordinators whose Lévy measures are represented as Laplace transforms of measures on (0,infinity), and refers to them as CME-subordinators. The study shows that the transition probabilities of such processes without drifts are absolutely continuous on (0,infinity) with respect to Lebesgue measure. It is also demonstrated that the densities are bounded in space-time and tend to zero as time goes to infinity, with the speed of decrease being closely related to the behavior near the origin of the corresponding Lévy density.
STOCHASTIC PROCESSES AND THEIR APPLICATIONS
(2024)
Article
Statistics & Probability
Jukka Lempa, Ernesto Mordecki, Paavo Salminen
Summary: This paper investigates the characteristics and properties of diffusion spiders and calculates the density of the resolvent kernel. The study of excessive functions leads to the expression of the representing measure for a given excessive function. These results are then applied to solving optimal stopping problems for diffusion spiders.
STOCHASTIC PROCESSES AND THEIR APPLICATIONS
(2024)
Article
Statistics & Probability
Kento Egashira, Kazuyoshi Yata, Makoto Aoshima
Summary: This study investigates the asymptotic properties of hierarchical clustering in different settings, including high-dimensional, low-sample-size scenarios. The results show that hierarchical clustering exhibits good asymptotic properties under practical settings for high-dimensional data. The study also extends the analysis to consider scenarios where both the dimension and sample size approach infinity, and generalizes the concept of populations in multiclass HDLSS settings.
JOURNAL OF MULTIVARIATE ANALYSIS
(2024)
Article
Engineering, Mechanical
Jiaxu Li, Ming Liu, Xu Yan, Qianting Yang
Summary: Wind pressure is essential for architectural design, and this study found that using different probabilistic distribution models can improve the accuracy of reference wind pressure calculation. In the research conducted in Liaoning Province, the extreme value type III model and moment method achieved the best fit. Additionally, probability density functions for wind speed and wind direction were established for further analysis of wind pressure.
PROBABILISTIC ENGINEERING MECHANICS
(2024)
Article
Statistics & Probability
Mirko D'Ovidio, Francesco Iafrate
Summary: This article explores the connection between elastic drifted Brownian motions and inverses to tempered subordinators, and establishes a link between multiplicative functionals and dynamical boundary conditions. By representing functionals of the drifted Brownian motion as the inverse of a tempered subordinator, the problem is simplified.
STOCHASTIC PROCESSES AND THEIR APPLICATIONS
(2024)
Article
Economics
Guangyuan Gao
Summary: This article proposes a new method for fitting the Tweedie model, which uses the EM algorithm to address heterogeneous dispersion and estimate the power variance parameter.
INSURANCE MATHEMATICS & ECONOMICS
(2024)
Article
Engineering, Mechanical
R. Allahvirdizadeh, A. Andersson, R. Karoumi
Summary: The operational safety of high-speed trains on ballasted bridges relies on preventing ballast destabilization. This study explores the impact of epistemic uncertainties on the system using ISRA. Neglecting these uncertainties can lead to overestimation of permissible train speeds and reduced system safety.
PROBABILISTIC ENGINEERING MECHANICS
(2024)
Article
Statistics & Probability
Neda Mohammadi, Leonardo Santoro, Victor M. Panaretos
Summary: This study considers the nonparametric estimation of the drift and diffusion coefficients in a Stochastic Differential Equation (SDE) using functional data analysis methods. The proposed estimators relate local parameters to global parameters through a novel Partial Differential Equation (PDE) and do not require any specific functional form assumptions. The study establishes almost sure uniform asymptotic convergence rates for the estimators, taking into account the impact of different sampling frequencies.
STOCHASTIC PROCESSES AND THEIR APPLICATIONS
(2024)
Article
Statistics & Probability
Seyed Mohammad Azimi-Abarghouyi, Harpreet S. Dhillon
Summary: This paper presents a novel variant of a Matern cluster process for biological nanonetworks. The researchers characterize the conditional distribution of the cluster process and compare the characteristics in three-dimensional space and two-dimensional space.
STATISTICS & PROBABILITY LETTERS
(2024)
Article
Statistics & Probability
Li Li, Pengfei Shi, Qingliang Fan, Wei Zhong
Summary: We investigate the estimation of causal effect in the presence of censored outcome and high-dimensional covariates. To enhance the efficiency of average causal effect estimation, we propose the censored outcome adaptive Lasso (COAL) for covariate selection.
STATISTICS & PROBABILITY LETTERS
(2024)
Article
Computer Science, Interdisciplinary Applications
Blake Moya, Stephen G. Walker
Summary: A full posterior analysis method for nonparametric mixture models using Gibbs-type prior distributions, including the well known Dirichlet process mixture (DPM) model, is presented. The method removes the random mixing distribution and enables a simple-to-implement Markov chain Monte Carlo (MCMC) algorithm. The removal procedure reduces some of the posterior uncertainty and introduces a novel replacement approach. The method only requires the probabilities of a new or an old value associated with the corresponding Gibbs-type exchangeable sequence, without the need for explicit representations of the prior or posterior distributions. This allows the implementation of mixture models with full posterior uncertainty, including one introduced by Gnedin. The paper also provides numerous illustrations and introduces an R-package called CopRe that implements the methodology.
COMPUTATIONAL STATISTICS & DATA ANALYSIS
(2024)
Article
Statistics & Probability
Yasuhito Nishimori
Summary: In this paper, we investigate the relation of hitting probabilities between two sets in Hunt processes, without considering spatial homogeneity. We claim that if the Hunt process satisfies the strong Feller property, then there is a certain relationship between the hitting probabilities of the two sets.
STATISTICS & PROBABILITY LETTERS
(2024)
