Results 41 to 50 of about 150 (129)

Modeling car‐following behaviors using a driving style–based Bayesian model averaging Copula framework in mixed traffic flow

Computer-Aided Civil and Infrastructure Engineering, Volume 40, Issue 21, Page 3316-3332, 29 August 2025.
Abstract As a fundamental driving behavior, the accurate modeling of car‐following (CF) dynamics is essential for improving traffic flow and advancing autonomous driving technologies. Due to the stochastic nature of CF behaviors, the CF model parameters often exhibit heterogeneity (multimodal trends), distribution uncertainty, and parameter ...
Shubo Wu, Yue Zhang, Yajie Zou, Yuanchang Xie, Yangyang Wang   +4 more
wiley   +1 more source

Bayesian Inference for Copula-Linked Bivariate Generalized Exponential Distributions: A Comparative Approach

Axioms
This paper addresses the limitations of existing bivariate generalized exponential (GE) distributions for modeling lifetime data, which often exhibit rigid dependence structures or non-GE marginals.
Carlos A. dos Santos, Saralees Nadarajah, Fernando A. Moala, Hassan S. Bakouch, Shuhrah Alghamdi   +4 more
doaj   +1 more source

Mean Distances and Dependence Structures for Lifetimes of Systems With Shared Components

Applied Stochastic Models in Business and Industry, Volume 41, Issue 2, March/April 2025.
ABSTRACT Distortion and copula functions represent powerful tools in the description of the reliability of some complex systems as functions of their components' reliability. On this aim, we study several pairs of reliability systems with one or more shared components, in the case when their lifetimes are independent and identically distributed or ...
Marco Capaldo, Antonio Di Crescenzo, Franco Pellerey   +2 more
wiley   +1 more source

On Optimization of Copula-Based Extended Tail Value-at-Risk and its Application in Energy Risk

IEEE Access, 2021
In this paper, we study a novel risk measure, which is a copula-based extension of tail value-at-risk (TVaR). This measure is called dependent tail value-at-risk (DTVaR), which is a generalization of TVaR.
Bony Parulian Josaphat, Moch Fandi Ansori, Khreshna Syuhada   +2 more
doaj   +1 more source

Semiparametric Copula‐Based Confidence Intervals on Level Curves for the Evaluation of the Risk Level Associated to Bivariate Events

Environmetrics, Volume 36, Issue 2, March 2025.
ABSTRACT If (X,Y)$$ \left(X,Y\right) $$ is a random pair with distribution function FX,Y(x,y)=ℙ(X≤x,Y≤y)$$ {F}_{X,Y}\left(x,y\right)=\mathbb{P}\left(X\le x,Y\le y\right) $$, one can define the level curve of probability p$$ p $$ as the values of (x,y)∈ℝ2$$ \left(x,y\right)\in {\mathbb{R}}^2 $$ such that FX,Y(x,y)=p$$ {F}_{X,Y}\left(x,y\right)=p ...
Albert Folcher, Jean‐François Quessy
wiley   +1 more source

Joint Probability Analysis of the Rich‐Poor Runoff and Sediment Discharge in Karst Watersheds

Water Resources Research, Volume 61, Issue 1, January 2025.
Abstract As one of the largest contiguous karst landscapes in the world, southwest China has experienced severe soil erosion because of its frequent climate extremes, special hydrogeology, shallow and discontinuous soil, steep topography, and inappropriate land use.
Jiayin Yao, Xingxiu Yu, Zhenwei Li, Shilei Peng, Xianli Xu   +4 more
wiley   +1 more source

An Alternative Type II Claims Pareto Model for Reliability and Bimodal Risk Analysis: Copulas, Properties, Mathematical Modeling, and Actuarial Case Study

Journal of Mathematics, Volume 2025, Issue 1, 2025.
This article aims to present a new type‐II claims Pareto extension for statistical reliability and actuarial analysis. The new probabilistic density can be simplified in terms of the baseline densities. Some new bivariate types were developed under some copula approaches.
Atef F. Hashem, Haitham M. Yousof, M. A. Abdelkawy, M. A. Abd Elgawad, Abdisalam Hassan Muse, Mohamed G. Khalil, Pramita Mishra   +6 more
wiley   +1 more source

Bivariate Power Lindley Models Based on Copula Functions Under Type‐II Censored Samples With Applications in Industrial and Medical Data

Journal of Mathematics, Volume 2025, Issue 1, 2025.
This study introduces three innovative bivariate models to address complex dependencies between random variables in real‐world applications. Specifically, we develop bivariate power Lindley (BPL) distribution models utilizing the Gumbel, Frank, and Clayton copulas.
Ehab M. Almetwally, Aisha Fayomi, Maha E. Qura, Pramita Mishra   +3 more
wiley   +1 more source

Quantifying compound flood event uncertainties in a wave and tidally dominated coastal region: The impacts of copula selection, sampling, record length, and precipitation gauge selection

Journal of Flood Risk Management, Volume 17, Issue 3, September 2024.
Abstract Coastal flooding is a growing hazard. Compound event characterization and uncertainty quantification are critical to accurate flood risk assessment. This study presents univariate, conditional, and joint probabilities for observed water levels, precipitation, and waves.
Joseph T. D. Lucey, Timu W. Gallien
wiley   +1 more source

Predicting failure times of coherent systems

Naval Research Logistics (NRL), Volume 71, Issue 5, Page 627-644, August 2024.
Abstract The article is focused on studying how to predict the failure times of coherent systems from the early failure times of their components. Both the cases of independent and dependent components are considered by assuming that they are identically distributed (homogeneous components). The heterogeneous components' case can be addressed similarly
Jorge Navarro, Antonio Arriaza, Alfonso Suárez‐Llorens   +2 more
wiley   +1 more source