Results 81 to 90 of about 4,426 (211)
Pruning and Truncating the Mixture R‐Vine Model Using the Mixture Weight
Journal of Probability and Statistics, Volume 2026, Issue 1, 2026.Vine copula mixture models are highly flexible and can handle complex hidden dependencies among variables without restricting the parametric shape of the margins or the type of dependency structure. But it loses flexibility as the number of dimensions increases. That is due to two main reasons.
Fadhah Alanazi, Marek T. Malinowski
wiley +1 more source
Structural Control and Health Monitoring, Volume 2026, Issue 1, 2026.The evolution pattern of dam deformation reflects its structural response and operational state. Analyzing this pattern enables effective identification of the probability of deformation anomalies. Deviation reflects the extent to which dam deformation deviates from its expected evolution pattern and serves as an important basis for identifying ...
Xudong Chen +8 more
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On bivariate Archimedean copulas with fractal support
Dependence ModelingDue to their simple analytic form (bivariate) Archimedean copulas are usually viewed as very smooth and handy objects, which should distribute mass in a fairly regular and certainly not in a pathological way. Building upon recently established results on
Sánchez Juan Fernández +1 more
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Dependence Modeling, 2013 We study the impact of certain transformations within the class of Archimedean copulas. We give some admissibility conditions for these transformations, and define some equivalence classes for both transformations and generators of Archimedean copulas ...
Di Bernardino Elena, Rullière Didier
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On generators in Archimedean copulas
Sahand Communications in Mathematical Analysis, 2017 Summary: This study, after reviewing construction methods of generators in Archimedean copulas (AC), proposes several useful lemmas related with generators of AC. Then a new trigonometric Archimedean family will be shown which is based on cotangent function. The generated new family is able to model the low dependence structures.
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ON GENERATING MULTIVARIATE SAMPLES WITH ARCHIMEDEAN COPULAS [PDF]
, 2014 Archimedean copulas are one of the most known classes of copulas. They allow modeling the dependencies between variables with small number of parameters.
Stelmach, Jacek
core +1 more source
Copula‐Based Deep Learning Models for Competing Risks
Statistical Analysis and Data Mining: An ASA Data Science Journal, Volume 18, Issue 6, December 2025.ABSTRACT This study introduces a novel approach to modeling competing risks in survival analysis by integrating learnable Copula functions (Clayton, Frank, and Gaussian) with deep learning architectures, including Convolutional Neural Networks (CNN), Long Short‐Term Memory (LSTM) networks, and a hybrid CNN‐LSTM model.
Jong‐Min Kim, Jihoon Kim, Il Do Ha
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BarekengSocial security benefits may not be enough for retirement. Equity release products like marriage reverse annuities can boost retirement income for older couples.
Arnhilda Aspasia Lundy +2 more
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Singularity aspects of Archimedean copulas
Journal of Mathematical Analysis and Applications, 2015 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Fernández Sánchez, Juan +1 more
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General Multivariate Dependence using Associated Copulas
Revstat Statistical Journal, 2016 This paper studies the general multivariate dependence and tail dependence of a random vector. We analyse the dependence of variables going up or down, covering the 2 d orthants of dimension d and accounting for non-positive dependence.
Yuri Salazar Flores
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