Results 11 to 20 of about 925 (187)
Why Are FGM Copulas Successful? A Simple Explanation
Advances in Fuzzy Systems, 2018 One of the most computationally convenient nonredundant ways to describe the dependence between two variables is by describing the corresponding copula.
Songsak Sriboonchitta, Vladik Kreinovich
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New asymmetric perturbations of FGM bivariate copulas and concordance preserving problems
Moroccan Journal of Pure and Applied Analysis, 2023 New copulas, based on perturbation theory, are introduced to clarify a symmetrization procedure for asymmetric copulas. We give also some properties of the symmetrized copula mainly conservation of concordance.
El maazouz Mohamed, Sani Ahmed
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Developing prediction models to estimate the risk of two survival outcomes both occurring: A comparison of techniques. [PDF]
Stat Med, 2023 Introduction This study considers the prediction of the time until two survival outcomes have both occurred. We compared a variety of analytical methods motivated by a typical clinical problem of multimorbidity prognosis. Methods We considered five methods: product (multiply marginal risks), dual‐outcome (directly model the time until both events occur)
Pate A +10 more
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Flexible use of copula-type model for dose-finding in drug combination clinical trials. [PDF]
Biometrics, 2022 Abstract Identification of the maximum tolerated dose combination (MTDC) of cancer drugs is an important objective in phase I oncology trials. Numerous dose‐finding designs for drug combination have been proposed over the years. Copula‐type models exhibit distinctive advantages in this task over other models used in existing competitive designs.
Hashizume K, Tshuchida J, Sozu T.
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Correcting for selection bias in HIV prevalence estimates: an application of sample selection models using data from population-based HIV surveys in seven sub-Saharan African countries. [PDF]
J Int AIDS Soc, 2022 Abstract Introduction Population‐based biomarker surveys are the gold standard for estimating HIV prevalence but are susceptible to substantial non‐participation (up to 30%). Analytical missing data methods, including inverse‐probability weighting (IPW) and multiple imputation (MI), are biased when data are missing‐not‐at‐random, for example when ...
Palma AM +13 more
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Constructing symmetric generalized FGM copulas by means of certain univariate distributions [PDF]
, 2004 In this paper we focus on symmetric generalized Fairlie-Gumbel-Morgenstern (or symmetric Sarmanov) copulas which are characterized by means of so-called generator functions.
Fischer, Matthias J., Klein, Ingo
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Advances in Applied Probability, 2023 AbstractCopulas provide a powerful and flexible tool for modeling the dependence structure of random vectors, and they have many applications in finance, insurance, engineering, hydrology, and other fields. One well-known class of copulas in two dimensions is the Farlie–Gumbel–Morgenstern (FGM) copula, since its simple analytic shape enables closed ...
Christopher Blier-Wong +2 more
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Risk aggregation with FGM copulas
Insurance: Mathematics and Economics, 2023 We offer a new perspective on risk aggregation with FGM copulas. Along the way, we discover new results and revisit existing ones, providing simpler formulas than one can find in the existing literature. This paper builds on two novel representations of FGM copulas based on symmetric multivariate Bernoulli distributions and order statistics.
Christopher Blier-Wong +2 more
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A new extension of bivariate FGM copulas [PDF]
Metrika, 2008 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Amblard, Cécile, Girard, Stéphane
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FGM Copula’s Extension Via Polynomial Function
Journal of Physics: Conference Series, 2020 Abstract This study is concerned with generalizing the well-known family of FGM copula in terms of a polynomial function. A general form of the FGM copula via a copula function is proposed in order to obtain a new FGM copula family. Various particular cases have been presented according to the degree of the polynomial function. Proofs of
Ahmed Al-Adilee, Ali Mohammed Mahdi
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